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empirical evidence

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National Center for Biotechnology Information - PubMed Central - Expert opinion vs. empirical evidence
LiveScience - Empirical evidence: A definition
Academia - Empirical Evidence

empirical evidence , information gathered directly or indirectly through observation or experimentation that may be used to confirm or disconfirm a scientific theory or to help justify, or establish as reasonable, a person’s belief in a given proposition. A belief may be said to be justified if there is sufficient evidence to make holding the belief reasonable.

The concept of evidence is the basis of philosophical evidentialism, an epistemological thesis according to which a person is justified in believing a given proposition p if and only if the person’s evidence for p is proper or sufficient. In this context , the Scottish Enlightenment philosopher David Hume (1711–76) famously asserted that the “wise man…proportions his belief to the evidence.” In a similar vein, the American astronomer Carl Sagan popularized the statement, “Extraordinary claims require extraordinary evidence.”

Foundationalists , however, defend the view that certain basic, or foundational, beliefs are either inherently justified or justified by something other than another belief (e.g., a sensation or perception) and that all other beliefs may be justified only if they are directly or indirectly supported by at least one foundational belief (that is, only if they are either supported by at least one foundational belief or supported by other beliefs that are themselves supported by at least one foundational belief). The most influential foundationalist of the modern period was the French philosopher and mathematician René Descartes (1596–1650), who attempted to establish a foundation for justified beliefs regarding an external world in his intuition that, for as long as he is thinking, he exists (“I think, therefore I am”; see cogito, ergo sum ). A traditional argument in favour of foundationalism asserts that no other account of inferential justification—the act of justifying a given belief by inferring it from another belief that itself is justified—is possible. Thus, assume that one belief, Belief 1, is justified by another belief, Belief 2. How is Belief 2 justified? It cannot be justified by Belief 1, because the inference from Belief 2 to Belief 1 would then be circular and invalid. It cannot be justified by a third nonfoundational Belief 3, because the same question would then apply to that belief, leading to an infinite regress. And one cannot simply assume that Belief 2 is not justified, for then Belief 1 would not be justified through the inference from Belief 2. Accordingly, there must be some beliefs whose justification does not depend on other beliefs, and those justified beliefs must function as a foundation for the inferential justification of other beliefs.

Empirical evidence can be quantitative or qualitative. Typically, numerical quantitative evidence can be represented visually by means of diagrams, graphs, or charts, reflecting the use of statistical or mathematical data and the researcher’s neutral noninteractive role. It can be obtained by methods such as experiments, surveys, correlational research (to study the relationship between variables), cross-sectional research (to compare different groups), causal-comparative research (to explore cause-effect relationships), and longitudinal studies (to test a subject during a given time period).

Qualitative evidence, on the other hand, can foster a deeper understanding of behaviour and related factors and is not typically expressed by using numbers. Often subjective and resulting from interaction between the researcher and participants, it can stem from the use of methods such as interviews (based on verbal interaction), observation (informing ethnographic research design), textual analysis (involving the description and interpretation of texts), focus groups (planned group discussions), and case studies (in-depth analyses of individuals or groups).

Empirical evidence is subject to assessments of its validity. Validity can be internal, involving the soundness of an experiment’s design and execution and the accuracy of subsequent data analysis , or external, involving generalizability to other research contexts ( see ecological validity ).

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3. Theories of grammar and language acquisition

3.7. Becoming a linguist: Empirical and theoretical arguments

There are two main kinds of arguments, empirical arguments and theoretical arguments. Empirical arguments are based primarily on observation of data, while theoretical arguments are based primarily on ideas. In this class, we will be using both. Often, more complex arguments combine both theoretical and empirical arguments.

Empirical arguments

Empirical arguments are based on data. They have three parts: make relevant observations, make a theoretical claim, and explain how your observations are related to your claim. The parts don’t have to be in this order, but they should be in an order that makes sense.

In this chapter, the fact that children’s knowledge of language is rule-based (as discussed in Section 3.3 ) is an example of an empirical argument. We observed examples of children’s behaviour, such as their response to corrections from their parents, their pluralization of nonce words , and their use of overregularization . Based on our observations, we concluded that children’s language is rule-based rather than memorized.

Making observations

When you make an empirical argument, you need to start by describing the surface properties of your data. You should be answering the question, “What are the non-controversial facts?” These are mostly observations that a non-linguist could make!

Some examples of observations that you might start which are relevant to morphology and syntax include:

What does the sentence mean?
Which nouns and pronouns in the sentence refer to the same entity?
Is the sentence ambiguous? In other words, does it have more than one meaning?
What is the word order? Which words precede or follow which other words?
Are other word orders possible?
Is the sentence grammatical?
What similarities are there between this word and other words?

There are lots of observations that you could make about any sentence, but you need to stick to the ones that are relevant to your theoretical claims.

Making a theoretical claim

Although an empirical argument is based on some observation, it leads you to make some theoretical claim about the structure of your data. In this part, you should be answering the question, “What conclusions can you draw based on your observations?” This is where you talk about things you can’t see or hear, but that you infer based on what you do see or hear.

Some examples of theoretical claims you might make in this course include:

Whether a word is simplex or complex .
The classification of a word or sentence based on its structure.
The part of speech of a word (e.g., whether a word is a noun or a verb), as we will learn about in Chapter 5 .
Whether a string of words behaves as a unit, which we will learn about in Chapter 16 .

Backing up your claim

To make a complete argument, you also need to explain how your your observations provide evidence for your claim. You cannot assume that your readers will be able to draw the same conclusions as you!

In some cases, you should also think about other claims people might think to make about the same data, and why your analysis is better.

Theoretical arguments

Theoretical arguments are based on ideas, logic, and reasoning, instead of data. Because of this, we can never trust them as much as empirical arguments. However, we wouldn’t be able to get as far in science without theoretical arguments, too!

In this chapter, the Poverty of the Stimulus argument in Section 3.4 is an example of a theoretical argument.

A theoretical argument has two parts: premises and a conclusion.

Laying out your premises

A theoretical argument is based on premises, which are the ideas that you use as a foundation to draw your conclusion. They are your claims about how things work. A premise can be a conclusion from a previous (theoretical or empirical) argument, or it can be an easily observable fact (e.g., language is infinite; humans acquire language; not all languages are the same).

For your argument to work, you need to be relatively certain that your audience will accept your premises.

The Poverty of the Stimulus argument has two premises: that language is infinite and that infinite systems are unlearnable.

One of the ways to argue against a theoretical argument is to claim that one (or more) of the premises is false.

Drawing a conclusion

Your premises should logically lead to a conclusion. It’s important that you actually state what that conclusion is, though, instead of making your readers figure it out.

Another way to argue against a theoretical argument is to claim that the conclusion does not actually follow from the assumptions.

Consider your assumptions

Every time you make an argument, you make theoretical assumptions. These can be foundational, like “I am assuming generative grammar is correct,” or structural, like “I’m assuming that two things can’t occupy the same spot,” or methodological, like “I’m assuming that grammaticality judgments are reliable.” A lot of times, we are making assumptions without realizing it, so it’s always good to spend some time thinking about what assumptions we are making.

Decide whether you should be making your assumptions, or whether you should dig deeper and investigate some of them. Sometimes it’s useful to make assumptions, though, to see where a theory will lead us, or because if we had to start from scratch with no assumption every time, we wouldn’t make it very far very fast.

Decide whether you need to state your assumptions. You don’t need to state any assumptions that you are pretty sure your audience shares. This happens a lot in a class setting—we share the assumptions of the class materials. You also don’t need to state any assumptions that are pretty obvious from your argument. But beware! Sometimes what is obvious to you will not be obvious to your reader. When in doubt, state your assumptions.

Presenting your argument

When you write an argument, you should clearly state all of the components of your argument and how they are connected.

Sometimes you will have to make a chain of arguments. For example, if we were to argue that a language has prepositions, we first have to identify an adposition and which noun it goes with, and then show that the adposition goes before that noun.

Sometimes a chain of argumentation will include both empirical arguments and theoretical arguments. For example, our argument that children use rule-based language actually has both empirical and theoretical components.

As you lay out all of the arguments in your line of reasoning and each of their components, think about what order it is best to lay out your claims. Do any of your points depend on another point?

Always make sure you use technical terminology where appropriate. Technical terminology is useful because it is normally concisely defined to avoid ambiguity. For example, saying un- is a morpheme is more precise than saying un- is part of a word.

Check yourself!

A made-up word for one-time use.

The process of applying a rule in contexts where it should not apply, common in child speech.

A word containing only a single morpheme.

A word containing two or more morphemes.

The Linguistic Analysis of Word and Sentence Structures Copyright © by Julianne Doner is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Empirical evidence: A definition

Empirical evidence is information that is acquired by observation or experimentation.

The scientific method

Types of empirical research, identifying empirical evidence, empirical law vs. scientific law, empirical, anecdotal and logical evidence, additional resources and reading, bibliography.

Empirical evidence is information acquired by observation or experimentation. Scientists record and analyze this data. The process is a central part of the scientific method , leading to the proving or disproving of a hypothesis and our better understanding of the world as a result.

Empirical evidence might be obtained through experiments that seek to provide a measurable or observable reaction, trials that repeat an experiment to test its efficacy (such as a drug trial, for instance) or other forms of data gathering against which a hypothesis can be tested and reliably measured.

"If a statement is about something that is itself observable, then the empirical testing can be direct. We just have a look to see if it is true. For example, the statement, 'The litmus paper is pink', is subject to direct empirical testing," wrote Peter Kosso in " A Summary of Scientific Method " (Springer, 2011).

"Science is most interesting and most useful to us when it is describing the unobservable things like atoms , germs , black holes , gravity , the process of evolution as it happened in the past, and so on," wrote Kosso. Scientific theories , meaning theories about nature that are unobservable, cannot be proven by direct empirical testing, but they can be tested indirectly, according to Kosso. "The nature of this indirect evidence, and the logical relation between evidence and theory, are the crux of scientific method," wrote Kosso.

The scientific method begins with scientists forming questions, or hypotheses , and then acquiring the knowledge through observations and experiments to either support or disprove a specific theory. "Empirical" means "based on observation or experience," according to the Merriam-Webster Dictionary . Empirical research is the process of finding empirical evidence. Empirical data is the information that comes from the research.

Before any pieces of empirical data are collected, scientists carefully design their research methods to ensure the accuracy, quality and integrity of the data. If there are flaws in the way that empirical data is collected, the research will not be considered valid.

The scientific method often involves lab experiments that are repeated over and over, and these experiments result in quantitative data in the form of numbers and statistics. However, that is not the only process used for gathering information to support or refute a theory.

This methodology mostly applies to the natural sciences. "The role of empirical experimentation and observation is negligible in mathematics compared to natural sciences such as psychology, biology or physics," wrote Mark Chang, an adjunct professor at Boston University, in " Principles of Scientific Methods " (Chapman and Hall, 2017).

"Empirical evidence includes measurements or data collected through direct observation or experimentation," said Jaime Tanner, a professor of biology at Marlboro College in Vermont. There are two research methods used to gather empirical measurements and data: qualitative and quantitative.

Qualitative research, often used in the social sciences, examines the reasons behind human behavior, according to the National Center for Biotechnology Information (NCBI) . It involves data that can be found using the human senses . This type of research is often done in the beginning of an experiment. "When combined with quantitative measures, qualitative study can give a better understanding of health related issues," wrote Dr. Sanjay Kalra for NCBI.

Quantitative research involves methods that are used to collect numerical data and analyze it using statistical methods, ."Quantitative research methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques," according to the LeTourneau University . This type of research is often used at the end of an experiment to refine and test the previous research.

Identifying empirical evidence in another researcher's experiments can sometimes be difficult. According to the Pennsylvania State University Libraries , there are some things one can look for when determining if evidence is empirical:

Can the experiment be recreated and tested?
Does the experiment have a statement about the methodology, tools and controls used?
Is there a definition of the group or phenomena being studied?

The objective of science is that all empirical data that has been gathered through observation, experience and experimentation is without bias. The strength of any scientific research depends on the ability to gather and analyze empirical data in the most unbiased and controlled fashion possible.

However, in the 1960s, scientific historian and philosopher Thomas Kuhn promoted the idea that scientists can be influenced by prior beliefs and experiences, according to the Center for the Study of Language and Information .

— Amazing Black scientists

— Marie Curie: Facts and biography

— What is multiverse theory?

"Missing observations or incomplete data can also cause bias in data analysis, especially when the missing mechanism is not random," wrote Chang.

Because scientists are human and prone to error, empirical data is often gathered by multiple scientists who independently replicate experiments. This also guards against scientists who unconsciously, or in rare cases consciously, veer from the prescribed research parameters, which could skew the results.

The recording of empirical data is also crucial to the scientific method, as science can only be advanced if data is shared and analyzed. Peer review of empirical data is essential to protect against bad science, according to the University of California .

Empirical laws and scientific laws are often the same thing. "Laws are descriptions — often mathematical descriptions — of natural phenomenon," Peter Coppinger, associate professor of biology and biomedical engineering at the Rose-Hulman Institute of Technology, told Live Science.

Empirical laws are scientific laws that can be proven or disproved using observations or experiments, according to the Merriam-Webster Dictionary . So, as long as a scientific law can be tested using experiments or observations, it is considered an empirical law.

Empirical, anecdotal and logical evidence should not be confused. They are separate types of evidence that can be used to try to prove or disprove and idea or claim.

Logical evidence is used proven or disprove an idea using logic. Deductive reasoning may be used to come to a conclusion to provide logical evidence. For example, "All men are mortal. Harold is a man. Therefore, Harold is mortal."

Anecdotal evidence consists of stories that have been experienced by a person that are told to prove or disprove a point. For example, many people have told stories about their alien abductions to prove that aliens exist. Often, a person's anecdotal evidence cannot be proven or disproven.

There are some things in nature that science is still working to build evidence for, such as the hunt to explain consciousness .

Meanwhile, in other scientific fields, efforts are still being made to improve research methods, such as the plan by some psychologists to fix the science of psychology .

" A Summary of Scientific Method " by Peter Kosso (Springer, 2011)

"Empirical" Merriam-Webster Dictionary

" Principles of Scientific Methods " by Mark Chang (Chapman and Hall, 2017)

"Qualitative research" by Dr. Sanjay Kalra National Center for Biotechnology Information (NCBI)

"Quantitative Research and Analysis: Quantitative Methods Overview" LeTourneau University

"Empirical Research in the Social Sciences and Education" Pennsylvania State University Libraries

"Thomas Kuhn" Center for the Study of Language and Information

"Misconceptions about science" University of California

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Speech Language Pathology Research Guide: Evidence Levels & Types

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Evidence Pyramid

Depending on their purpose, design, and mode of reporting or dissemination, health-related research studies can be ranked according to the strength of evidence they provide, with the sources of strongest evidence at the top, and the weakest at the bottom:

Secondary Sources: studies of studies

Systematic Review

Identifies, appraises, and synthesizes all empirical evidence that meets pre-specified eligibility criteria
Methods section outlines a detailed search strategy used to identify and appraise articles
May include a meta-analysis, but not required (see Meta-Analysis below)

Meta-Analysis

A subset of systematic reviews: uses quantitative methods to combine the results of independent studies and synthesize the summaries and conclusions
Methods section outlines a detailed search strategy used to identify and appraise articles; often surveys clinical trials
Can be conducted independently, or as a part of a systematic review
All meta-analyses are systematic reviews, but not all systematic reviews are meta-analyses

Evidence-Based Guideline

Provides a brief summary of evidence for a general clinical question or condition
Produced by professional health care organizations, practices, and agencies that systematically gather, appraise, and combine the evidence
Click on the 'Evidence-Based Care Sheets' link located at the top of the CINAHL screen to find short overviews of evidence-based care recommendations covering 140 or more health care topics.

Meta-Synthesis or Qualitative Synthesis (Systematic Review of Qualitative or Descriptive Studies)

a systematic review of qualitative or descriptive studies, low strength level

Primary Sources: original studies

Randomized Controlled Trial

Experiment where individuals are randomly assigned to an experimental or control group to test the value or efficiency of a treatment or intervention

Non-Randomized Controlled Clinical Trial (Quasi-Experimental)

Involves one or more test treatments, at least one control treatment, specified outcome measures for evaluating the studied intervention, and a bias-free method for assigning patients to the test treatment

Case-Control or Case-Comparison Study (Non-Experimental)

Individuals with a particular condition or disease (the cases) are selected for comparison with individuals who do not have the condition or disease (the controls)

Cohort Study (Non-Experimental)

Identifies subsets (cohorts) of a defined population
Cohorts may or may not be exposed to factors that researchers hypothesize will influence the probability that participants will have a particular disease or other outcome
Researchers follow cohorts in an attempt to determine distinguishing subgroup characteristics

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Oromotor Nonverbal Performance and Speech Motor Control: Theory and Review of Empirical Evidence

Affiliation.

1 Department of Communication Sciences & Disorders, University of Wisconsin-Madison, Madison, WI 53706, USA.
PMID: 37239240
PMCID: PMC10216469
DOI: 10.3390/brainsci13050768

This position paper offers a perspective on the long-standing debate concerning the role of oromotor, nonverbal gestures in understanding typical and disordered speech motor control secondary to neurological disease. Oromotor nonverbal tasks are employed routinely in clinical and research settings, but a coherent rationale for their use is needed. The use of oromotor nonverbal performance to diagnose disease or dysarthria type, versus specific aspects of speech production deficits that contribute to loss of speech intelligibility, is argued to be an important part of the debate. Framing these issues are two models of speech motor control, the Integrative Model (IM) and Task-Dependent Model (TDM), which yield contrasting predictions of the relationship between oromotor nonverbal performance and speech motor control. Theoretical and empirical literature on task specificity in limb, hand, and eye motor control is reviewed to demonstrate its relevance to speech motor control. The IM rejects task specificity in speech motor control, whereas the TDM is defined by it. The theoretical claim of the IM proponents that the TDM requires a special, dedicated neural mechanism for speech production is rejected. Based on theoretical and empirical information, the utility of oromotor nonverbal tasks as a window into speech motor control is questionable.

Keywords: dysarthria; nonverbal motor control; oromotor; speech motor control; speech production; task specificity.

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PMC10216469

Oromotor Nonverbal Performance and Speech Motor Control: Theory and Review of Empirical Evidence

1. Introduction

1.1. historical perspective.

The significance of nonspeech, oromotor control for theories of speech motor control, and for the clinical diagnosis and management of speech motor control deficits have long been written about in the literature. Relevant publications extend back in time in the literature at least to the 1940, when Emil Froeschels (1884–1972), one of the original academic speech pathologists, advocated chewing as a therapeutic technique for stuttering and other speech disorders [ 1 , 2 ]. (I use Froeschels as a blurry reference point in time for the beginning of “academic” publications on the topic of oromotor nonspeech postures and gestures and their relationship with speech (and voice) production. An earlier example was published in 1893 by Oskar Guttman in a book titled, Gymnastics of the Voice, a method for song and speech, also a method for the cure of stuttering and stammering [ 3 ]. This second edition in English, translated from a version (one of at least four), was originally written in German. Guttman, writing on exercises for the tongue, (which he claimed most people regarded as no more than a “helpless lump of meat” (p. 83), suggested back and forth tongue tip movements between the corners of the mouth, slowly at first and gradually ramping up to maximum speed. Examples of other tongue exercises (among 16) included protrusion–retraction cycles and rapid “dotting” of the upper lip with the point of the tongue. Lip exercises included practice for independent movements of the upper and lower lip and a velar exercise of raising and lowering the soft palate with the mouth open wide. Close reading of Guttman’s book suggests it was intended more for singers than speakers, but he clearly meant the oromotor nonverbal exercises to apply equally to speech, as suggested in the subtitle of the book. Other similar manuals and textbooks were written in the late nineteenth and early twentieth centuries. They are written still today). For Froeschels [ 2 ], the act of silent (mimed) chewing, especially with exaggerated movements of the tongue and lips, harkened back to the biological origins of modern voice and speech production. Preverbal people discovered that these motions could be superimposed on sound made in the throat, resulting in vocal tract signals that changed with the motions. Chewing, in Froeschel’s view, took a patient back to the most basic of oromotor behaviors, a logical starting point for voice and speech therapy. Froeschels (Ref. [ 1 ], p. 127) offered this anecdote as evidence for this view: “…gum chewing played an interesting part in my studies on the influence of chewing on voice and speech. Two years ago, my wife and I made a trip on a Greyhound bus. The drivers changed regularly, and the new driver always addressed the travelers. I could then predict to my wife, without a single error, whether or not the driver chewed gum, making the differential diagnosis from the impression of a hyperfunctional or a hypofunctional voice, on the one hand, or of a normal voice, on the other. The normal voice indicated to me that the man was used to chewing gum”. The shared anatomical structures for chewing and speech production led Froeschels to claim, “In fact, only one single center (in the anterior central convolution of the brain) dominates the movements of chewing and talking. It stands to reason that two different functions cannot be performed at the same time by one single part of the body. From this, we can conclude that, as far as the movements of the mouth are concerned, what has been considered two functions, namely talking and chewing must be one and the same” (Ref. [ 2 ], p. 9). (The paper appeared in [ 2 ] and is reprinted in Froeschels’ Selected Papers of Emil Froeschels, 1940–1964 [ 4 ]). As discussed below, Froeschel’s views are a variation on the common effector arguments for the relevance of oromotor nonverbal control to speech motor control [ 5 , 6 ]; see the discussion in [ 7 ]. Obviously, you can chew and speak at the same time, as evidenced by the millions of mothers and fathers who have told their children not to. (A close reading of Froeschels publications on the near identity of motor control for chewing and speech suggests some inconsistencies in his thinking about doing two different things simultaneously with shared effectors. Usually, his view is the one expressed above, but at least one example of a different opinion, that you can chew and speak at the same time, can be found in the chewing papers collected by Froeschels [ 4 ]. The book also contains papers on deafness, psychoanalysis, stuttering, aphasia, and language characteristics).

Froeschels seemed to regard chewing and speaking, or any other combination of simultaneous oral actions, as subtasks of oral control. This I discuss below in Section 5 . Task Specificity.

1.2. Purposes of the Present Paper

This essay has several purposes. Because the different purposes are often interconnected, their order as presented in the current section is not meant to correspond exactly with the sequence of sections that follow. Potential relationships between oromotor nonverbal behaviors and matters such as swallowing and sleep apnea are not considered here.

One purpose of this paper is to outline general issues concerning nonspeech oromotor (NSOM) tasks and their relationship with speech production. These considerations include the difference between the differential diagnosis of neurological diseases versus speech production deficits secondary to those diseases. Selected facts concerning speech production in neurologically healthy speakers and speakers with dysarthria are also discussed.

A second purpose is to provide an evaluation of NSOM tasks, also identified throughout this paper as oromotor nonverbal tasks, and how they are thought to relate to speech production. I argue that a significant amount of contemporary research and clinical practice embraces the broad outlines of Froeschel’s view, with potential for more sophisticated and nuanced measurements (see [ 7 ], for discussion of the limits of instrumented speech analysis in clinical settings). For example, in many cases, the study and assessment of oromotor nonverbal control does not require an examiner’s perceptual judgment of observed behavior but can be quantified with instrumental techniques if they are available [ 8 ]. Componential (presumed single structure) evaluation of oromotor, nonverbal control, either observational or less frequently quantified via instruments, is used in the clinic, as exemplified by tasks such as soundless or syllabic diadochokinesis (DDK) to evaluate both rate and rhythmic control of the lips, tongue, jaw, and vocal fold movements. Quantitative assessment of other behaviors such as maximum force (F) or pressure (P; P = F/unit area) to estimate the strength of individual oral mechanism components and the rate of cyclic movement (such as opening and closing the jaw or wagging the tongue back and forth at the maximum rate or repeating voiced syllables at the maximum rate) are also thought to provide useful information on speech production deficits and their treatment. In short, this section addresses the possibility of reconciling performance on NSOM tasks and speech production phenomena among neurologically healthy speakers and speakers with dysarthria.

As reviewed by Ziegler [ 9 ] and Weismer [ 6 ], a central assumption of the view that NSOM tasks are relevant to speech motor control is that shared anatomical structures imply some degree of shared control for different functions. The assumption has been made most typically for peripheral structures such as the tongue, lips, and jaw. More recently, it has been pushed upstream in functional imaging research, in which partially overlapping regions of the brain are active for both speech and nonspeech gestures or their sequencing. In either case, the overlap of structure or activity is taken as evidence for a degree of common control (e.g., Refs. [ 10 , 11 ] see critique of this logic in [ 12 ], pp. 135–136). In Weismer [ 6 ], this is called the “common effectors” fallacy. Herein, I replace “fallacy” with “assumption” to correct the implication of conclusiveness suggested by “fallacy”. The basic question to be addressed is the possibility of reconciling the information derived from NSOM tasks with speech production data.

A third purpose is to provide a sketch of the important distinction between the use of NSOM tasks to diagnose neurological disease versus speech production deficit. To the best of my knowledge, the literature does not contain an in-depth discussion of this issue. I believe that this diagnostic distinction is likely to be at the heart of the potential for NSOM tasks to further understanding of speech production deficits in dysarthria, and more generally to develop and refine theories of speech motor control [ 13 ].

A fourth purpose is to identify and evaluate publications that report empirical data on the relationship between oromotor nonverbal tasks and measures of speech production in both neurologically healthy speakers and speakers with motor speech disorders. These tabulated summaries ( Table 1 and Table 2 ) are intended as an extension of Tables II and III in Weismer [ 6 ].

Finally, brief consideration is given to cyclic tasks such as silent, rapid sequences of vocal tract opening and closing, or the same task with voiced syllables. Another example is rapid tongue wagging at maximum rate although a speech-like correlate of this NSOM task, unlike the case of silent and voiced syllables, is not obvious. These are examples of diadochokinetic DDK tasks, which have been used extensively in the clinical evaluation of motor speech disorders, as well in the literature on motor speech disorders and in neurotypical speakers and speakers with other kinds of speech disorders; this issue is addressed only briefly because of a recent extensive review of DDK [ 13 ].

Is it necessary to write more about this issue? I believe it is, for the following reasons. First, NSOM tasks are used frequently in clinical settings. Since the publications of Ziegler [ 9 , 14 ] and Weismer [ 6 ], several publications [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 ] point to the frequent use of oromotor nonverbal tasks in clinical settings, while acknowledging the absence of empirical evidence to support their use for speech production. Surveys of the use of NSOM tasks reported by previous researchers [ 15 , 17 , 24 ], while a decade or more old, are consistent with opinions offered in the studies cited above that the clinical use of NSOM tasks continues with essentially no empirical support. The issue continues to be debated in more recent literature [ 19 , 25 , 26 , 27 ].

Much of what follows is congruent with questions raised by Ziegler et al. [ 7 ], and the implications of empirical work described in a series of publications. As noted by Ziegler et al., these data raise serious doubts concerning the value of NSOMs in understanding the speech deficit in dysarthria. Theoretical issues also bear on the potential relationships between NSOM tasks and speech production: “…unresolved theoretical issues compel us to challenge the diagnostic value of nonspeech parameters in the clinical assessment of a patient’s motor speech impairment. The most general theoretical question is to what extent the organization of motor behavior differs between speaking and other orofacial motor activities…as well as the particularities of motor goal setting and of sensorimotor principles in specifying speech motor functions over other motor functions of the speech musculature” (Ref. [ 7 ], p. 21, emphasis added).

2. Definitions

2.1. operational definitions formulated for the purposes of this paper.

The following definitions are not meant to improve those for the same or similar terms in other publications.

Several definitions are revisions of ones in Weismer [ 6 ]. In his 2017 publication, Maas claimed that a problem with the oromotor nonspeech/speech production controversy is the absence of precise definitions required to frame the debate [ 26 ]. Precisely stated (but nevertheless arguable) definitions of the terms, “dysarthria”, “Mayo Clinic approach”, “oromotor nonverbal tasks”, “quasi-speech tasks”, and “explanation” are given in Weismer [ 6 ]. Herein, I revise and broaden definitions for “dysarthria”, “oromotor non-speech tasks”, and “quasi-speech tasks”. New definitions are provided for “task specificity”, “apraxia of speech”, and “speech motor control”, which surprisingly (to the author as well) were not formally included in Weismer [ 6 ] but see page 329). A brief note follows some of the definitions.

2.1.1. Speech Motor Control

Speech motor control is defined as the goal-directed, nervous system control of speech production by which movements, and their derivatives, effect shapes and configurations of structures throughout the speech mechanism, including laryngeal and respiratory structures, all planned and executed as a function of time to produce sequences of acoustic phonetic events for the purpose of communication. Acoustic phonetic output of the vocal tract is an integral component of speech motor control processes, not separate or subtractable from them. The speech acoustic signal is intertwined with the movements and their derivatives stated above by calibrating the latter with the former, and the former with the latter. Note : The claim that the speech acoustic output is the goal of speech motor control is based on the work of Guenther [ 28 ], Perkell [ 29 ] and Hickok and Poeppel [ 30 ]. See Bose and van Lieshout [ 31 ] for a different view.

2.1.2. Motor Speech Disorder

A motor speech disorder is a neurologically based disorder of speech motor control in which movements of the upper airway structures (including the velopharynx) and the constrictions and configurations they produce, as well as movements of the laryngeal and respiratory structures, and/or the planning and programming of those movements, are affected in ways that result in a speech acoustic signal that is phonetically and/or prosodically degraded and therefore cause deficits in speech intelligibility and/or naturalness. Note : “Neurologically based disorders” are those demonstrated on imaging studies (e.g., as in stroke, or multiple sclerosis) or those inferred from signs and symptoms (e.g., as in Parkinson’s disease or childhood apraxia of speech). Examples of signs of a speech motor control disorder include, but are not limited to, disorders of speaking rate, speech rhythm, sound-segment production, speaking fundamental frequency and/or sentence-level pitch modulation, prominence of syllables for lexical stress, and regulation of speech loudness.

2.1.3. Dysarthria

Dysarthria is a type of motor speech disorder, primarily regarded as an execution deficit resulting from muscle weakness, abnormalities of muscle tone, timing and coordination, in which the speech deficit is secondary to documented neurological damage resulting from a number of different diseases. Different types of dysarthria, developed in the perceptual studies of Darley, Aronson, and Brown [ 32 ] and refined by Duffy [ 33 ], are thought to be associated with damage to different parts of the nervous system. Note : As documented below, a reliable match between speech symptoms and dysarthria type, or between speech symptoms and disease diagnosis, has not received much support in the literature. This calls into question the suggestion of different speech therapies according to dysarthria type [ 33 ] as well as the frequent use of dysarthria or disease type as an experimental blocking variable.

2.1.4. Apraxia of Speech

Apraxia of speech (AOS) is a speech planning or programming dysfunction, as in the preparation of a sequence of syllables ahead of their production. AOS is a motor speech disorder in which the speech deficit is not thought to be the result of muscle weakness, tone abnormalities, and so forth. AOS is therefore different from dysarthria, although a simultaneous diagnosis of apraxia of speech and dysarthria can be made in the same patient. In this paper, AOS is not considered in depth.

2.1.5. Oromotor, Nonverbal Tasks (Nonspeech Oromotor (NSOM) Tasks)

Any performance task, absent phonetic goals, in which structures of the speech mechanism—especially those of the upper airway—are measured for any aspect of force production (maximum force, ‘‘fine’’ (submaximal) force, positional or force accuracy and/or hold duration (endurance), stability, repetition rate, impulse production, tone, range of motion, speed of motion, movement repetition rate and regularity, structural shape/configuration (e.g., lip rounding), and/or tracking accuracy). Note : The term and its acronym “Nonspeech oromotor” (NSOM) is in frequent use in the literature, most often to describe treatments used in the speech clinic, many of which are manualized for clinician use [ 34 ]. Nonspeech tasks performed by speech structures that are not part of the upper airway, such as laryngeal and respiratory structures, have also been studied, but are not discussed here.

2.1.6. Task Specificity

In motor control, task specificity is accomplished by flexible “tuning” of sensorimotor processes within nervous system networks to achieve a specific behavioral action/goal. Task-specific tuning is implemented by differential activity within the motor control network of fiber tracts and/or cortical and subcortical cells connected by these tracts. The tuning is learned and refined with extensive “practice” to achieve the desired goal; in the case of speech production, “practice” is not used in the sense of mastering a musical instrument or sports skill, rather it is embedded in the production of millions of utterances. The goal of speech motor control is to generate an acoustic phonetic output of the vocal tract that serves the purpose of communication. Note : This definition does not equate “tunings of networks” with specific structures and/or mechanisms; as discussed in Section 5 . Task Specificity.

2.1.7. Quasi-Speech Tasks

Tasks performed, on command, in which structures of the speech mechanism produce phonetic (or phonetic-like sounds, as in sustained vowels or fricatives), single syllables that are not words, diadochokinetic (DDK) tasks using repetition of a single syllable (e.g., /pʌpʌpʌ…/), or syllables with varying phonetic content (e.g., /pʌtʌkʌ…/), or sequences of other novel sounds or phonatory events, which have no lexical or paralinguistic function. Quasi-speech tasks may also include maximum and minimum fundamental frequency (F0), maximum and minimum phonatory intensity as a function of voice F0, F0 glissandos at different rates of change, and a variety of other sounds (e.g., raspberries, hissing sounds, rhythmic sequences of mouth sounds). Note . Quasi-speech tasks are difficult to define as the question of what is lexical or paralinguistic is subject to debate. For example, an argument can be made for hissing as lexical and/or paralinguistic, depending on context. The sound of hissing is not a word but may serve a communication purpose just like the word “hiss”. Ziegler et al. [ 7 ] refer to these quasi-speech events as non-speech, which in the current opinion is a reasonable way to categorize these productions. Quasi-speech is used in this paper for these events instead of non-speech because it is relevant to the idea of a continuum of tasks ranging from clearly not speech, to increasingly more speech-like events until the endpoint, “speech” is reached (see [ 35 ] discussion of different DDK tasks as points along such a continuum). The common factor among various quasi-speech tasks is that they require production of an acoustic signal, which may or may not be phonetic. The definition is not meant to apply to prelingual children because they may produce segmental and phonatory behaviors before understanding the directions to perform such tasks. Ziegler et al. [ 7 ] refer to repetitive syllable tasks as “nonspeech” tasks. I mostly agree with that classification—DDK tasks are not speech in the sense that they are not composed of sounds meant to be comprehended—but choose to use the narrower term to include other tasks as listed above.

2.1.8. Subsystems

Partitions of peripheral speech mechanism structures conceptualized as independent, functional components of speech production. Note: The partitions take various forms in the literature. These are considered further in Section 4 . Two Models of Speech Motor Control.

2.1.9. Mechanism

Nervous system processes for control of action; in the case of speech motor control, the neural processes organized and tuned to produce an acoustic signal having phonetic value for communication.

3. Preliminary Considerations

3.1. diagnosis of disease versus speech production deficit.

I make a critical distinction in this paper between the potential role of oromotor nonverbal tasks in the diagnosis of disease versus an understanding of global and specific speech production deficits associated with (secondary to) neurological disease (Ref. [ 36 ]; see review in [ 37 ]). This distinction would be unnecessary if type of dysarthria, or neurological disease, predicted global or specific characteristics of a speech motor control deficit. However, neither dysarthria nor disease type yields such reliable mappings, with possible exceptions in very mild or very severe dysarthria. To date, there is scant evidence that the performance on oromotor nonverbal tasks predicts disease or dysarthria type, or global and specific aspects of a speech motor control disorder. By “global aspects”, I mean (at least) type and severity of dysarthria, based on human judgments (Judgments of dysarthria type, even by SLPs and other trained professionals (e.g., neurologists) are not reliable as demonstrated in several experiments (e.g., Refs. [ 38 , 39 ]). In many experiments in dysarthria, whatever the level of analysis (e.g., kinematic, acoustic perceptual), type of dysarthria is a classification variable, wherein type is determined with the revised Mayo Clinic approach) (e.g., Refs. [ 38 , 39 , 40 ] or by automated analysis [ 41 ]). “Specific aspects” of a speech motor control disorder include the observation of dysfunction at the electromyographic, kinematic, aerodynamic, acoustic, and/or perceptual levels of analysis. Several research and clinical questions arise when considering the potential relationship between oromotor nonverbal performance and specific aspects of speech production. For example, does performance on an oromotor nonverbal task, or a set of such tasks, predict specific aspects of articulatory movement for speech production among speakers with dysarthria and/or acoustic characteristics of segmental production? Or does such performance predict particular substitution/distortion/omission patterns? Most importantly, do oromotor nonverbal tasks have predictive value for speech intelligibility deficits? These predictions can be reversed, as well; for example, does disease or dysarthria type predict performance on oromotor nonverbal tasks?

To the best of my knowledge, experiments to address focused questions such as these have not been conducted or have not been published. Only a handful of studies have explored an association between nonverbal, oromotor performance and speech measurements at any of the levels of analysis noted above. For those that have been reported, the majority failed to find a meaningful association between the two (see Table 1 and Table 2 , in Section 6 . Empirical Findings). Surprisingly, even fewer publications report comparisons of oromotor, nonverbal performance among different dysarthria or neurological disease types [ 42 , 43 , 44 ]. These studies are discussed further in the Section 6 “Empirical Findings”. (Here, “diagnose a neurological disease” means the use of the traditional cranial nerve examination to diagnose neurological disease on the basis of oromotor dysfunction, as well as tests of reflexes, limb and hand movements, and imaging studies. However, the distinction between diagnosing a neurological disease versus a dysarthria, or more broadly a disease from the cranial nerve examination is not so straightforward. The type of dysarthria or specific aspects of speech production deficits (as discussed in text) have not been predicted from the results of a cranial nerve examination or performance on any other set of orofacial nonverbal tasks or rapid syllable repetitions [ 45 ]. Interestingly, in a 2015 survey of SLPs who were asked to rate which assessments provided the most valuable information on speech intelligibility in adults with dysarthria, the oral mechanism examination, cranial nerve examination, and DDK were each ranked substantially more valuable compared with several standardized tests in which speech is the focus (Ref. [ 23 ], see their Figure 4). A similar survey finding was reported for SLTs in the UK [ 46 ]).

The issue of diagnosis of disease versus dysarthria type is important in experimental work. For example, dysarthria type is used as a classification variable in many experiments (e.g., [ 42 , 47 , 48 ], disease type in others (e.g., [ 49 , 50 , 51 ]). A smaller group of studies use classification variables that are a hybrid of dysarthria and disease types [ 37 ]. Dysarthria type, as determined on the basis of the revised Mayo Clinic approach [ 33 ], is most often based on judgments made by SLPs and/or neurologists. Dysarthria types are not assigned on the basis of objective rubrics, which in theory could be derived from Darley, Aronson, and Brown [ 32 ] and Duffy [ 33 ], but rather on global perceptual impressions of speech samples, possibly combined with results from a cranial nerve exam, nonspeech signs (i.e., limb tone), and knowledge of the underlying disease diagnosis. For example, “Two speech-language pathologists (SLPs) concurred the dysarthria type was consistent with the underlying medical diagnosis” (Ref. [ 37 ], p. EL210). This is all well and good, but the logic in classifying dysarthria type is somewhat circular because speakers in the dysarthria database used by Lansford et al. [ 37 ] were chosen to represent the classic features of the individual dysarthrias [ 32 , 33 ]. Spastic dysarthria, for example, may be inferred from a diagnosis of upper motor neuron disease, ataxic dysarthria from cerebellar disease, and so forth (see example in [ 37 ]; related reviews are provided in [ 36 , 52 ]). However, such inferences are not particularly reliable, as indicated previously [ 38 , 39 , 52 ]. Different approaches to the problem of dysarthria classification have been reported; see [ 53 ] (free classification) for an alternate approach to classifying dysarthria type with acoustic measures, and [ 54 ] for automatic classification of dysarthria type.

Classification of dysarthria type based on the Mayo Clinic system, or based on a combination of disease type and perceptual analysis, extends to the clinic where it may be used to formulate treatment plans [ 33 ] For example, the assumed underlying neuropathologies in flaccid versus spastic dysarthria may suggest an orofacial strengthening program in the former but not the latter [ 33 ]. In the case of flaccid dysarthria, the progress of a strengthening program can be tracked quantitatively with measurements derived from instruments such as the Iowa Oral Performance Instrument (IOPI). In spastic dysarthria, on the other hand, strengthening is regarded as contraindicated. Unfortunately, there is no evidence one way or the other for the efficacy of strengthening oral structures to improve outcome measures such as speech intelligibility or speech severity, or “specific” measures of articulatory performance (see Section 3.1 , above).

3.2. Can Performance on Oromotor Tasks Be Reconciled with Speech Production Deficits in Diseases/Dysarthrias?

This section focuses on the relationship between NSOM tasks and speech production characteristics in dysarthria but is relevant as well to speech motor control in neurotypical speakers. Similar observations on this issue are available in [ 7 ].

The challenge of reconciling oromotor nonverbal performance with speech motor control disorders is a recurring finding that across disease/dysarthria groups, many kinematic, acoustic, and perceptual phenomena are similar, not different. Surprisingly, as noted by [ 36 , 55 ], in contrast to studies in which a group of speakers with one type of disease/dysarthria is compared to neurologically healthy speakers, few studies have compared movement and/or acoustic characteristics among groups of people with different types of neurological diseases/dysarthrias.

A study of lip motion for single word utterances produced by speakers with Parkinson’s disease, Huntington’s Disease, cerebellar atrophy, upper motor neuron disease, and control speakers showed, for the most part, similar kinematic measures (amplitude, stiffness, acceleration/deceleration) among the four clinical groups and the control speakers. When significant differences were found, they were typically for comparisons between the group with cerebellar disease and the control speakers [ 49 ]. In another study [ 56 ], kinematic measures of inter-articulatory coordination between the lips and tongue for /u/ in the word “suit” were essentially the same for control speakers and speakers with amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD) (see [ 57 ], for a similar result based on acoustic coarticulatory measures obtained from speakers with multiple sclerosis (MS), PD, and neurologically healthy controls).

Speaking rates for groups representing each of the Mayo Clinic dysarthria types [ 33 ] were lower than the rates for neurologically healthy control speakers, but similar among the dysarthria groups [ 58 ] and diadochokinetic rates for speakers classified as having spastic and ataxic dysarthria were significantly slower than typical but not different from each other [ 59 ]. (Of note, in [ 59 ] a significant difference was obtained between the spastic and ataxic dysarthria groups in the variability of DDK sequences, with greater variability observed for the spastic group. This result, plus the statistically similar rates for the two disease/dysarthria groups, were contrary to the expectations from the Mayo classification system: Speakers with ataxic dysarthria were expected to have more variable speech rhythm than those with spastic dysarthria, and speakers with spastic dysarthria were expected to have slower rates than speakers with ataxic dysarthria. The authors comment that these findings require some reconsideration of dysarthria-type classification based on perceptual analysis). Vowel space areas for speakers with PD and ALS were statistically equivalent but smaller compared with neurotypical speakers [ 60 ]; second formant (F2) transition slopes were statistically equivalent in speakers with PD and stroke, but more shallow than slopes of neurologically healthy speakers [ 61 ]; voice-onset times for the three (English) voiceless stops produced in diadochokinetic sequences by speakers with the flaccid, spastic, ataxic, and hypokinetic types of dysarthria were similar across groups with the exception of /t/, for which speakers with ataxic dysarthria had longer VOTs compared to the other groups [ 48 ]. (These VOT data were derived from the well-known, original Mayo Clinic recordings from which the classification system was derived. There is no control group in the Morris study, and the variability of VOT measures was high, likely a result of variation in dysarthria severity and a combination of within- and across-speaker variability (each syllable within a 2.4 s sample from the full DDK sequence was measured for VOT, contributing multiple tokens for each speaker). In addition, the extent to which VOT values extracted from DDK sequences are representative of VOT measured in words in a carrier phrase, sentences, or read or spontaneous speech is another consideration for cautious interpretation of these results. See similar comments on the Morris [ 48 ] study in [ 62 ]).

Perceptual analyses of segmental errors in dysarthria are rare. One study compared vowel and consonant error patterns in Australian English of adults with the spastic and dyskinetic types of cerebral palsy and found no difference in the patterns except for greater severity among the dyskinetic group [ 63 ]. Speech intelligibility scores are not relevant to this discussion because they largely function as a metric of speech severity [ 64 ], which can vary in any disease/dysarthria type and therefore have little value in differentiating types.

Results of more recent publications are consistent with those of the aforementioned papers: speech production measures in speakers with dysarthria are typically different from those of control speakers, and infrequently different among disease/dysarthria groups. Studies consistent with this claim include (but may not be limited to) [ 7 , 47 , 50 , 52 , 53 , 55 , 65 , 66 , 67 , 68 , 69 ]. The inclusion of [ 47 ] in this claim is inferred from Figure 3 in [ 47 ], in which measures of F2 slope overlap considerably for eight different dysarthria “subtypes”. Correlation coefficients between maximum anterior tongue pressures and F2 slope were significant for the flaccid and mixed subtypes, but not significant for the other six subtypes. The results of [ 47 ] are discussed further in Section 6 . Empirical Findings).

Substantial differences among disease/dysarthria groups in severity, speech material, presence or absence of a control group, and measurement type complicate direct comparisons among these studies. In some studies, variables such as speech intelligibility for different groups of speakers with dysarthria are not reported [ 47 ]. In at least three studies, relative speech severity, as measured by speech intelligibility scores or ordinal scale scores, was unbalanced across groups [ 50 , 65 , 70 ]. Across studies, speech materials from which measures were derived ranged from DDK [ 48 ] to single words [ 69 ], phrases [ 53 ], and passage reading [ 70 ].

Several of these studies included multiple measures (e.g., [ 71 ]), some of which were statistically different among groups whereas others were statistically equivalent. The present claim is that the weight of the evidence from the citations above favors a view that statistical similarities are more frequent than differences across multiple disease/dysarthria groups. Whether or not statistical significance was found for “better” (i.e., more sensitive) measures than those that were similar, or that one type of difference, such as of kinematic speeds, is more or less informative than, say, a measure that captures rhythmic characteristics across phrase level material, is unknown.

As suggested above, the speech production similarities among different disease/dysarthria types may reflect potential “core” features of speech production deficits in dysarthria [ 36 , 52 ]. The potential for dysarthria/disease-specific speech production characteristics is also likely, if not assured, given the ability of experienced clinicians and researchers to identify different dysarthria types even if not with a high degree of inter- and intra-listener agreement. In either case, it is not clear how performance on NSOM tasks can be designed to reveal similar and different phonetic deficits among disease/dysarthria types.

Three examples highlight the challenge of mapping oromotor nonverbal performance to speech production events. First, accuracy of vocal tract shape for vowels, rhotics, and laterals, as well as local perturbations to these shapes such as constriction location and geometry for obstruent production, are clearly important for segmental integrity and its effect on speech intelligibility (Refs. [ 52 , 72 , 73 ]; see discussion in [ 74 ], pp. 575–578). Moreover, how would an NSOM task be designed to shed light on whole-tongue curvature in vowel and rhotic production [ 75 , 76 , 77 ] or tongue shape and groove configuration for fricatives [ 78 , 79 ]? Second, what kind of oromotor nonverbal task (or quasi-speech task; see [ 26 ]), might capture the specific rhythmic structure of a language? Finally, how might stability of an oromotor nonverbal task map on to the many stabilities and variabilities in segmental and prosodic speech tasks? Variability in speech production occurs at many levels, including articulator positions for different consonants (e.g., Refs. [ 80 , 81 , 82 ]), coordination between two articulators for a particular segment and even across segments (coarticulation, also referred to as coproduction), sentence-level timing (see review in [ 83 ]), and the many acoustic phonetic outputs related to segmental and prosodic characteristics of the speech signal. Many of the articulatory variabilities for vowel segments such as /u/ and the lax vowels [ 84 ] and rhotics and liquids [ 85 , 86 ] are in the service of acoustic stability; in this sense, these are “good” variabilities. How might an oromotor nonverbal task be designed to distinguish “good” from “bad” variabilities, where “positive” variabilities are those in the service of segmental integrity and “negative” variabilities disrupt that integrity?

Suggestions have been made to design oromotor, nonspeech tasks relevant to speech motor control by creating tasks as similar to speech production as possible (e.g., Ref. [ 25 ]). In this view, oromotor non-speech capabilities are imagined to be arrayed along a continuum from gestures or efforts very different from speech motor control performance, to gestures and efforts very much like those observed in speech motor control, but without phonetic identity. Examples of the former include performance in maximum articulator strength, force stability, and rate of cyclic, non-verbal articulatory movement. Suggestions for the latter oromotor nonverbal tasks recognize the need to mirror the inherent time varying nature of phonetic gestures and their product, speech acoustic gestures [ 31 , 87 ], or the production of “silent” speech gestures (articulatory miming) such as raising the tongue tip to make contact with the alveolar ridge as in apical stops [ 25 ]. The relevance of a possible continuum of NSOM tasks to speech production behavior is discussed more fully in the next section.

4. Two Models of Speech Motor Control

4.1. integrated model (im) versus task specific/task dependent model (tsm/tdm).

Over the past six decades, many models or theories of speech motor control have been put forth (in the current paper, the terms “model” and “theory” are used interchangeably with full recognition of the important technical distinction between the two). Two models with implications for the relevance of oromotor nonverbal behavior to articulatory behavior are discussed here. The Integrated Model (IM) and the Task-Specific or Task Dependent Model (TSM, TDM) are at odds in this debate. They are worth discussing because they each have potential value in guiding the development of experimental hypotheses that are relevant to theories of speech motor control and clinical practice. Other, more formal (computational) models of speech motor control are available [ 28 , 88 ], and in fact, the IM and TDM share some assumptions with these models.

Models that differ in assumptions and content are tested against each other by contrasting predictions. The best-known example of prediction “contests” in speech science research pits the motor theory of speech perception against “auditory” theories of speech perception (for review, see [ 89 , 90 ]). In brief, the original formulation of the motor theory held that in humans, a species-specific, dedicated brain module served the function of speech perception [ 91 , 92 ]. The module does not use general auditory mechanisms in the brain to perceive speech. Rather, the module represents the objects-to-be-perceived as articulatory gestures—phonetic identities. These identities are automatic outputs of the module, and do not require transformations of the physical signal entering the central auditory pathways. The module, a product of evolution, is dedicated to the perception of speech and reflects the tight coupling in humans of speech production and speech perception. In contrast, auditory theories of speech perception suggest that general auditory mechanisms are employed to perform the perception of speech in humans, much as they are assumed to be for the perception of any auditory event; a special, species-specific analysis mechanism is not required.

The two theories of speech perception make opposing experimental predictions. The motor theory predicts that animals should not respond to variations in speech stimuli in the same way as humans—animals do not possess the special mechanism that would allow them to do so. In contrast, auditory theories predict the perception of speech signals is likely to be similar in both animals and humans because both use general auditory mechanisms to process the signals. This is a simplified statement of opposing predictions made by the two theories, but in general the predictions are consistent with their contrasting structure. Other theories of speech perception exist as well but are not discussed here; see [ 89 , 90 ].

This brief presentation of a well-known theoretical debate between special versus non-dedicated mechanisms in speech perception is directly relevant to the structure and predictions derived from the IM and TDM. The IM and TDM make opposing predictions as well, some as clear cut as the one just described for the case of speech perception. In this section, I show how the structure of the IM and TDM generate these predictions. To the best of my knowledge, previous publications on the nonspeech-speech issue have not described explicitly such predictions and how they derive from the respective structures of the models. Ironically it is possible the specificity of the opposing predictions presented below must be regarded as tentative because they are derived from two “models” that lack specificity.

The current structure of both the IM and TDM do not qualify as true models. More precisely, both are sets of statements that resemble assumptions, like primary premises in deductive reasoning. Both qualify as coarse-grained theoretical frameworks, with the proviso that a widely accepted definition of “theoretical framework” has been difficult to establish for research on speech motor control (see [ 93 ]).

When an SLP employs oromotor nonverbal or quasi-speech tasks to diagnose and/or treat a speech production deficit in a person with dysarthria, it is reasonable to ask, what are the reasons for this choice? Stated otherwise, what evidence is available and defensible for the effectiveness of oromotor nonverbal tasks in diagnosing a speech production disorder in dysarthria, or treating it with such tasks. (It is interesting that in the surveys that have been done on the use of oromotor nonverbal tasks in diagnosis and treatment of motor speech disorders, the data have focused primarily on whether or not the tasks are used, rather than why SLPs use them [ 15 , 22 ]. Models and theories, even if provisional, are important to how this question is answered. I do not discount the value of clinician experience in choosing a diagnostic or treatment approach. An SLP’s experiential database of therapeutic outcomes, and what seems to have caused (or not caused) them is important and should be included as a significant component of clinical decision making [ 94 , 95 , 96 ].

The structures of the IM and TDM are described first, followed by the predictions emerging from these structures. A later section describes how data in the literature related to these predictions support either (or both) theoretical frameworks.

4.1.1. Structure of IM

The IM assumes, explicitly, that general motor processes are recruited for the production of speech. “Ziegler has interpreted our position as a task-independent model of motor control and in particular of speech motor control…we believe our model is better described as an integrative model in which some nonspeech motor tasks share principles with speech and some do not—that is, the speech motor system is integrated into a more general motor system. This leads us to postulate overlapping neural and behavioral systems for the control of speech and volitional nonspeech tasks” (Ref. [ 97 ] p. 38). Linguistic units such as phonetic segments are independent of motor processes; a domain-independent motor system transforms the units to action. By “domain-independent” motor processes, I mean motor control mechanisms that are not specialized for specific actions, such as (for example) speech production, playing an instrument, or finger spelling. Rather, the motor control capabilities of the nervous system are sufficiently powerful and flexible to be recruited and shaped for any and all actions. To be fair, Ballard et al. [ 97 ] allow that overlap of motor control for volitional, nonspeech and speech behavior is only partial, in that some nonspeech tasks are relevant to speech motor control, others are not. Which nonspeech tasks are not relevant to speech motor control are not suggested. Ballard, Granier, and Robin (Ref. [ 98 ] p. 983, emphasis added) put this view succinctly: “We rely on such theoretical stances as that presented by Folkins and Bliele (1990) and Saltzman (1986) which claim that the motor system is not necessarily organized around presumed units of language or speech. Rather, it is assumed that the motor system has its own cognitive architecture that is activated and monitored, in part, by the language system”. Speech motor control is therefore thought to be based on principles common to general movement control, regardless of what the movement is in service of. Similar views, though more nuanced for the case of speech motor control are presented in [ 99 , 100 ].

This nesting assumption, criticized for the case of speech motor control in [ 6 ], and more recent publications (e.g., Ref. [ 7 ]), drives the idea that speech motor control can be studied most directly by eliminating the speech acoustic signal that results from movement of the articulators, larynx and respiratory system. The speech acoustic signal is linguistic (e.g., Ref. [ 101 ]) and should be separated from evaluation of the movement control that generates linguistic events--phonetic behavior (e.g., voice onset time [VOT], vowel, diphthong, nasal, and semivowel formant frequencies), the various acoustic contributors to word and sentence stress, speech timing, and so forth. Stated otherwise, these “linguistic” events are not in the domain of speech motor control. In addition, the assumption eliminates, to a large extent, the relevance of movement type to understanding its control. Oromotor nonverbal tasks, whatever form they take, are stripped of the complexity of speech production movements (such as multi-articulator coordination over time and space) and therefore capable of allowing a basic analysis of effector control. In other words, such tasks are designed to move the analysis up to the top of the hierarchy—the general principles of motor control, free of specific goals.

It follows that IM rejects the idea that processes and perhaps the anatomy of speech motor control are modular (see [ 102 , 103 ]). It has been argued that “speech is not special”—echoing the theoretical difference between the motor theory of speech perception and auditory theories—and so does not require speech tasks to study and understand speech motor control (Ref. [ 26 ], p. 347). As argued below, the proper study of speech motor control requires tasks that include an acoustic phonetic, linguistically relevant product of underlying movements and forces, but in no way requires a specialized speech production neural module parallel to the one proposed in the motor theory of speech perception.

The IM also assumes that measures of speech motor control are well-served by measures of the parameters mentioned above (e.g., force, distance, tracking ability), in both oromotor nonspeech and speech tasks. Such measures have been used extensively in studies of finger, hand, arm, leg, and other non-oral motor behaviors, and in oromotor behavior as well.

Another assumption of IM is that a logical study of speech motor control, as well as other motor control tasks, is performed by isolating components of an ensemble of peripheral effectors that are organized to produce speech and other oromotor behaviors. This view is motivated by two explicit, supporting assumptions. One is that different orofacial subsystems—meaning the lips versus jaw, the jaw versus tongue, and lips versus tongue, the velopharyngeal port versus any of these structures “Subsystems” is used here following [ 8 ]. Rong et al. [ 104 ] have used the term to include the respiratory, phonatory, resonatory, and articulatory subsystems, which is more consistent with typical textbook descriptions of how the speech mechanism is partitioned [ 105 ]—can be differentially impaired in dysarthria. For example, speakers with dysarthria may have different degrees of impairment distributed across subsystems, often referred to as “differential impairment of the articulators” [ 103 , 106 ]. As discussed in Weismer [ 6 ], for this concept to make sense requires measurement of each isolated subsystem impairment, followed by a quantitative model that combines the results across the designated subsystems to estimate the likely deficit of the integrated, upper airway effector ensemble in the production of speech. The measurement of “isolated” subsystem impairment, seen through the lens of the IM, must be performed with oromotor nonspeech tasks, because in speech production, movements of the lips, tongue, and jaw do not function independently. Weismer (Ref. [ 6 ], p. 321) cited a passage from [ 107 ] endorsing this view. Subsystem movements of the lips, jaw, and tongue for speech production are coordinated over time and space, and, in the case of the jaw and tongue, and lower lip and jaw, are coupled anatomically and functionally, albeit in a loose-to-moderate way that depends on the speech sound (or syllable) production goal. It may be argued that tongue and lip movements can be isolated from movements of the jaw during speech, by fixing the position of the latter with a bite block. However, the matter of fixing the jaw in one position and therefore neutralizing it as a contributor to articulatory events is more complicated than it seems at first glance. Folkins and Zimmermann [ 108 ] showed that electromyographic (EMG) signals from jaw closer muscles were present for phonetic events requiring closure of the vocal tract, even when jaw position was fixed with a bite block. More recently, Dromey, Richins, and Low [ 109 ] reported the qualitative observation that, in their bite block experiment, some participants occasionally “bit down” on the block when they produced sentences. Although Dromey et al. did not specify when the participants did this, it would be interesting to know if the bitedowns were intermittent, possibly timed to phonetic events that in speech require closure of the vocal tract. Isolating the jaw, tongue, or lips during speech production, with all parts moving, does not seem to be possible, at least not currently. Weismer (Ref. [ 6 ], pp. 320–322; pp. 332–333) presents other significant problems with subsystems analysis. It should be pointed out that [ 104 ] performed an analysis of each component of more traditionally defined subsystems (respiratory, phonatory, resonatory, and articulatory) using multiple speech and speech-like measures. Rong et al. tested a tentative hypothesis for their participants with ALS that the measures for each subsystem represented its isolated impairment for speech production.

4.1.2. Predictions from the IM

Predictions concerning speech production deficits follow from the structure and assumptions of the IM.

First, the IM predicts that a componential analysis of at least the three upper airway subsystems (tongue, lips, jaw) will provide useful information regarding a person’s oral communication skills. The prediction should apply to both speech intelligibility scores, as a “general” measure of speech deficit, and its underlying (“specific”, as discussed in Section 3.1 ) phonetic details, such as perceptually determined segmental errors [ 63 ] or automated estimates of segment “goodness” derived from the speech acoustic signal [ 110 ]. A challenge for this prediction is, as discussed above, the absence of a suitable metric of the overall deficit of orofacial muscular control based on componential analysis. This is so because the problem of “summing” the deficits of the three (or more) isolated parts and expressing the sum as an index of overall oromotor deficit has not been attempted and may not be conceptually feasible. (I am not arguing that the problem has zero potential to be resolved; “not attempted” does not strictly mean it has not been tried, but the absence of any such publications in the literature suggests either the absence of an attempt or, if attempted, a lack of success. However, a long-term research program can be envisioned to establish the proper way to express deviation from “normal” for each subsystem, perhaps using different tasks and establishing the best ones from the large number of potential oromotor, nonspeech gestures (see [ 6 , 25 ]). The research program could pursue formulae that combine subsystem component deficits that predict an overall, quantitative deficit of upper articulatory function for speech production, and even one that might account for specific speech sound deficits. How subsystem impairments that are quantitatively similar (e.g., 20% deviation from normal function for each subsystem) are combined for an estimate of overall oromotor deficit is a major issue that would need to be resolved. There is no a priori reason to expect 20% deviation from normal in a jaw oromotor nonverbal task to mean the same thing to speech production as a 20% deviation in tongue performance. A long-term goal would be to show that the quantitative nonspeech deficit maps onto speech intelligibility measures. I am not favorably inclined to this sort of work, because I think the effort would ultimately be futile. However, we all have our opinions, and in the end, a carefully developed proposal for this kind of work requires fair consideration; science is so much more valuable than opinion. Instrumental measures for the nonspeech behaviors would be far preferable for the work, but my use of “…perceptual and/or instrumental methods” is meant to acknowledge the often-used requests to patients to, “wag your tongue back and forth as fast as possible”, “open and close your mouth as fast as possible”, “press your tongue into your cheek as hard as you can, resist the pressure I apply”, and so forth. In Ziegler et al. [ 7 ], multi-task performance, including speech and non-speech tasks (by their definition DDK is considered a non-speech task), addresses a similar question by performing a statistical analysis on a large group of speakers with dysarthria and showing that speech and non-speech performance form mutually exclusive groupings).

Second, based on the continuum notion of NSOM tasks, ranging from very different from speech movements (e.g., steady force efforts exerted by each of the upper airway articulators, including the measurement of maximum forces or pressures, and/or endurance of maintaining maximum or submaximum forces), to movements that are similar to speech production gestures (e.g., soundless gestures like those observed for phonetic segments), performance on more speech-like NSOM tasks should predict speech intelligibility scores and phonetic “goodness” more accurately when compared with less speech-like tasks. A problem with this experiment is identifying how components (subsystems) of oromotor control can be partitioned for time-varying tasks, such as a soundless lingua-alveolar gesture.

The IM makes predictions for the treatment of neurogenic speech production disorders, which follow from the predictions outlined above for their diagnosis. For example, the componential assumption predicts that training of oromotor skills, in the absence of phonetic output of the vocal tract, will result in improved speech production skills either globally (e.g., improved speech intelligibility) and/or locally (e.g., at the segmental level of analysis). Implications of the IM for componential, oromotor training at the segmental level, such as training focused on the lips for improvement of labial consonant production or configuration for vowels, are (to the best of my knowledge) not considered explicitly in publications advocating the IM, but data have been published that are not consistent with the hypothesis [ 7 , 111 , 112 ].

Finally, a strong form of the IM predicts that therapy with a goal of improving articulatory skills in persons with dysarthria will be equally effective by training NSOM tasks versus NSOM tasks plus articulation, or NSOM tasks plus auditory training. The “NSOM task alone” condition would have to be paired with another form of non-oromotor training performance (e.g., a rhythm or reaction time task) to balance the conditions comparisons.

4.1.3. Structure of the TDM

Ziegler [ 14 ] presents a “task-dependent model” (TDM) of speech motor control. The TDM contrasts with what he calls a “task-independent model”, which is similar if not identical to the IM. Stated otherwise, the “task-independent” model is consistent with the recruitment of general motor processes, as defined above, to implement the movements, forces, and sensorimotor mechanisms observable in speech production. In contrast, Ziegler’s task-dependent view is that speech motor control is implemented by motor processes unique to speech production. Ziegler argues that speech motor control is unlike motor control for non-verbal, oromotor actions such as those listed in a compendium published in [ 25 ].

The structure of the TDM, as currently developed, is coarse-grained in the same way as the IM. Like the IM, the model is best described by a series of statements, rather than by a more formal structure.

First, in the TDM, sensorimotor control processes for speech production are qualitatively different from those for oromotor control of non-speech actions. Motor control processes for the actions produced by structures of the speech mechanism are specific to speech production. In this view, the idea of a continuum of oromotor movements and configurations that vary in similarity to those required to produce speech does not make sense. Importantly, the sensorimotor processes in the TDM—that is, in speech motor control—include the speech acoustic signal and its integration with respiratory, laryngeal, velopharyngeal and articulatory movements, applied forces, and configurations. They also include sensorimotor processes for generating and regulating airflows and pressures and integrating them with movements and configurations. Sensorimotor processes in the TDM, including feedback from the speech acoustic signal and tactile and proprioceptive sensors (among other sensory information from structures of the upper airway, larynx, and respiratory system) are not separable from the gestures observed in speech production. They are an integral component of speech motor control [ 28 , 29 ].

Second, the TDM as currently conceptualized does not specify in precise neural terms how task dependency fits in with speech motor control processes. One possibility, discussed above, is that a dedicated nervous system network of nuclei and fiber tracts serves as the mechanism of speech motor control (i.e., it is a module). An alternative is that speech motor control may be vested in a learned and overpracticed “tuning” of interconnected nuclei and fiber tracts, developed from early childhood on, repeatedly refined by the millions of calibration samples and refinements that come with talking.

Third, the listener’s requirements for an intelligible speech signal enter the domain of, but not necessarily mechanisms for, speech motor control. These requirements are part of the goals of speech motor control, in the sense that they can dictate details of the task. Speaking metaphorically, the TDM allows, by alternate tunings of the neural substrate for oral communication, the speaker to know and adapt to what the listener needs [ 113 ].

Finally, the TDM is not consistent with the componential approach to the study of speech motor control. In the TDM, the goals of speech production—the production of acoustic signals useful for communication—are not accomplished by independent mappings of subsystem oromotor nonverbal performance to specific phonetic segments.

4.1.4. Predictions of TDM

Several predictions emerge from the TDM that are opposite to those from the IM. First, the TDM predicts that measures of oromotor control for isolated structures such as the lips, tongue, and jaw, derived from non-speech actions,: will not predict an overall or detailed analysis of a speech production deficit, either summed across the structures or within single structures. A measure of verbal deficit in speech motor control is speech intelligibility, or other coarse-grained perceptual measures including but not limited to scaled estimates of severity. A “detailed analysis” might include perceptual evaluation of speech sound accuracy and prosodic characteristics, acoustic measures of different classes of speech sounds, measures positions, displacements, and velocities of movable upper airway structures or analysis of imaged tongue positions or configurations (such as ultrasound imaging: see Section 3.1 ). Stated otherwise, the TDM predicts that componential analysis will not sum to yield a variable that will predict speech intelligibility, or the accuracy of speech sounds, even when the evaluation of a specific, isolated component is matched to a speech sound group. For example, in the TDM perspective isolated evaluation of the tongue by means of oromotor, nonspeech gestures will not predict the correctness of tongue gestures for lingual consonants.

The TDM suggests several clinical predictions. For example, in a properly controlled experiment, therapeutic gains in speech production skills of persons with dysarthria should be greater among a group of individuals receiving speech production training, compared with persons trained to improve oromotor, nonverbal skills. An alternative version of this experiment is to compare therapeutic gains across two groups, one receiving oromotor, nonverbal training plus speech production training, the other speech production training plus training of a motor skill that does not involve oromotor structures, such as control of a measure of handgrip (e.g., target accuracy, or stability). The design of experiments such as these present challenges, many of which concern experimental control variables across groups such as comparability of severity, clinician competence, and stability of the underlying disease responsible for dysarthria. Assuming the experiment can be controlled, the concept of the latter experiment is probably closer to clinical reality than the former, which compares only oromotor, nonverbal training to speech production training.

Another prediction consistent with the TDM reverses the IM prediction that measures of oromotor, nonverbal control can be summed across subsystems to estimate the magnitude of a deficit in speech motor control. More precisely, estimates of overall speech motor control deficits, by speech intelligibility and/or severity scores, will not predict performance of oromotor, nonverbal control, summed across subsystems. A more fine-grained version of this prediction is that obstruent errors that differ in magnitude across place of articulation, will not predict the presence of differential weakness, displacement, speed, and so forth, in NSOM tasks that parallel the place-specific phonetic impairment.

4.2. Structure and Predictions from the IM and TDM: Summary

The IM and TDM have been discussed here because of their explicit application to theoretical and clinical understanding of motor speech disorders. Neither the IM nor TDM are true models; rather, both are a series of statements and assumptions that offer coarse-grained accounts of typical and impaired speech motor control in dysarthria (as well as in other speech deficits not covered here).

Selected experimental predictions derived by the current author from the structure and assumptions of the IM and TDM have been presented. Comparison of the predictions from the IM and TDM shows them to be in conflict. This is good for scientific and clinical communities, because the experimental evaluation of well-defined, opposing predictions should contribute to a qualitative, and eventually quantitative enhancement and refinement of either (or both of) the IM or TDM.

The IM and TDM have been described here as if separated by an impermeable conceptual wall. This is overly simplistic, but a starting point from which to determine experimentally if and how the two views can be melded (e.g., see [ 100 ]). Some formal models of speech motor control may represent execution goals in articulatory terms, such as vocal tract constriction location and degree, but the output of the model is an acoustic signal (Ref. [ 88 ], their Figure 1). Moreover, the speech acoustic signal is used to refine the shape, location, and degree of constriction—much as in Guenther’s [ 28 ] formal model. Nevertheless, a model with two (or more) simultaneous goals, even if not independent, may point the way to a hybrid model of speech motor disorders with IM and TDM principles.

5. Task Specificity

5.1. task specificity introduction.

An overarching issue in the potential link between oromotor nonverbal performance and speech production is the concept of task specificity, also referred to in the literature on motor speech disorders as task dependency. Task specificity, defined and discussed above as a critical difference in the motivating principles underlying the IM and TDM, is intertwined with the roles of common effectors, componential analysis of the mechanism of motor control, and functional goals in speech motor control.

5.2. Dystonia as a Task Specific Disorder

The concept of task specificity is not unique to speech motor control and its disorders. Focal dystonia, a motor control disorder in which unwanted, sustained muscle contraction results in distorted positions and postures of the trunk, legs, and arms, as well as cranial structures, may occur for a single effector and be restricted to one action (i.e., task). Examples of task-specific motor disorders include writer’s cramp and oromandibular dystonia. The single effectors in these disorders—the hand in writer’s cramp, the jaw in oromandibular dystonia—are manifest by involuntary, sustained contractions upon performance of a specific action. Writer’s cramp, in which the hand cramps immediately (or nearly so) when writing begins, does not affect the performance of other actions for which the hand is the primary effector [ 114 ]. Oromandibular dystonia is associated with involuntary, opening, closing, and sideway movements of the jaw, and in some cases, twisting movements of the lips and tongue. The involuntary muscle contractions are triggered by movements of the jaw and/or speech; the symptoms are often absent during sleep [ 115 ]. Both of these focal dystonias may be accompanied by tremors. Spasmodic dysphonia (SD) is regarded as a focal laryngeal dystonia, sharing with other focal and generalized dystonias the apparent absence of a motor disorder in certain tasks, and severe motor deficits in others. For example, in SD, the vocal folds appear on laryngoscopy to be normal and symmetrical at rest (during rest breathing), but during phonation for speech undergo or are subject to spasm-like contractions that interrupt the production of consonants and vowels. In other words, the clinical presentation of spasmodic dysphonia includes task specificity, that is, spasms triggered by speech production, but not other phonatory behaviors such as laughter and yawning [ 116 ]. Reference [ 32 ] included spasmodic dystonia as a dysarthria subtype of “hyperkinetic dysarthria”. Studies of the speech/voice production characteristics of hyperkinetic dysarthria are not frequent, possibly due to the relative rarity of dystonia compared with neurological diseases underlying other subtypes of dysarthria (e.g., Parkinson disease and hypokinetic dysarthria; upper motor neuron disease and spastic dysarthria). In a review of studies of isolated dystonia and dysarthria, published between 1976 and 2020, ref. [ 117 ] identified approximately 30 papers, 22 of which concerned persons with spasmodic dysphonia. Three papers reported data for persons with cervical dystonia; a single study of dysarthria in oromandibular dystonia was found. A reasonable conclusion is that task specificity is a familiar observation in neurological disease and in some cases is a requirement for certain diagnoses.

Focal dystonias highlight the importance of action goals, the latter integral to motor control. The goal is an integral part of motor control, not an independent, subtractable result of it. Stated otherwise, action goals are integral to motor control rather than an external result of it. Effectors are embedded in action goals; goals are not embedded in effectors.

5.3. Motor Learning and Task Specificity

Recently, the motor learning literature has seen a rapid growth of publications in which complex skills are studied. A recurring theme in this literature is the question of best training methods for skill acquisition and/or refinement. A frequent comparison is the training of basic motor capabilities, such as strength, or speed, to functional training in which the target skill is practiced. A recent review of the role of task specific, action control for hand positions, during tasks such as reaching, makes the case for a network of neural circuits within which the relative weights of neural activity in multiple networks are adjusted depending on the current hand position and its role in achieving a goal [ 118 ]. Successful accomplishment of the goal—such as grasping a cup—depends on movement control of the hand, wrist, and eyes. The authors] argue against decomposing the act of reaching into “parts”, such as eliminating visual input from an experiment to “isolate” the control of movement required for a reaching goal. Refs. [ 119 , 120 , 121 ] present similar views for task-specificity of motor control for actions other than speech at neural, physiological, and behavioral levels of analysis.

Rehabilitation of motor control disorders resulting from stroke and other acquired neurological disorders appears to be more efficient and effective when therapy is geared toward task-specific practice. As noted in [ 122 ], meaningless, repetitive actions, such as extensive practice of limb tone control, induce less effective improvement than practice of specific tasks that have meaning for an individual, such as walking. In animals, task specific training has been shown to induce more extensive cortical reorganization compared with repetitive tasks such as strengthening and tone control. Refs. [ 123 , 124 , 125 ] are additional sources for the superiority of task-specific versus non-task specific approaches in training motor skills in general as well as rehabilitation training for adults with acquired neurological disorders; see also [ 126 ].

5.4. We Are Talking about Task Specificity

Task specificity in neurologically typical and disordered speech motor control is a reasonable, if not obvious claim, not only based on the evidence reviewed above from the nonspeech, non-oromotor literature, but also based on theoretical arguments and published data. One of the centerpieces of the IM, in fact, is contradicted by the incompatibility of the evidence from this literature with that centerpiece. Specifically, the IM invokes “general” motor mechanisms as the basis of speech motor control, thus justifying pieces of the perspective, such as componential analysis and separation of action outcomes from the underlying processes of speech motor control. This implicates the control of general motor mechanisms in the study of any motor behavior—why speech motor control should be special compared to other actions such as reaching, walking, and sports skills is not at all clear. Thus, the incompatibility of the IM with the task-specific nature of speech motor control is inconsistent with data from other types of motor control, in which task-specificity is clear. According to the IM logic, this should not be the case. For best understanding in the IM view, analysis of motor control for reaching, walking, grasping, and producing many forms of music—for example, piano, guitar, zither—should be by separation of the actions into components with reduction of analysis of componential performance to measures such as maximum strength. The goals of these actions, which are musical outcomes, should be eliminated from such analyses. A “strong” form of the IM is defeated by its own assumptions.

Maas [ 26 ], following closely arguments made in [ 97 ], questions the ability to distinguish between tasks such as “speech” and “nonspeech”. More broadly, he is skeptical of the ability to define what a task is, and by implication the ability to contrast them as separate variables in an experiment. He bases this position on what I believe to be misinterpretation and misrepresentation of statements made in the relevant literature.

For example, Maas [ 26 ] and Ballard et al. [ 97 ] view the concept of “task specificity”—they use the term “task dependency”—in typical and disordered speech motor control as connected with the idea that speech is special . Ballard et al. [ 97 ] state, “Thus, it may not be the case that speech motor control is part of a task dependent system (i.e., speech is not special), but rather built from the family of motor processes that makes differences in behaviors related to tasks emerge” (p. 46). Admittedly, the meaning of this quote, relative to the current debate, is not clear. It could be taken as support for a tunable network (“a family of motor processes”) that reflects flexibility in function, and so allows a non-special speech production module to control variations in speech production behavior. Maas’ view is more nuanced but leans heavily on the notion that proponents of the TDM (or similar views) must invoke a module-like plant for the production of speech. However, the “speech is special” notion, in which speech motor control is vested in a special brain module has never been much of a player in speech production theories. A target article in which the evolution and current human underpinnings of speech motor control, including laryngeal and articulatory behavior, presents a case for the ontogenetic, functional reorganization of motor loops during the development of vocal tract control [ 127 ]. The target article, thirty commentaries on it, and the authors’ response make no mention of the kind of special, dedicated speech module like the one proposed for the motor theory of speech perception. More generally, such a module—dedicated and impermeable to other functions—has not, to my knowledge, been proposed for speech production. Thus, the equation of a task-specific (task dependent) perspective on speech motor control with the requirement for a special module is a straw man. Calling into question the definition of speech tasks, what they are and how they are nearly impossible to identify and distinguish from one another, distracts from the genuine issues. The implication that a “special mechanism” is required for any variation on oromotor behavior that results in varying forms of acoustic output from the vocal tract, is completely—and wrongly—dependent on the assumption that the TDM requires a special speech production module for every speech production task It is a reductio ad absurdum argument.

5.5. Accounting for Task Specificity without a Special Module

What are the neural alternatives to speech motor control vested in a special mechanism? A clue from scientists who study motor control of limb and hand actions and their underlying control for complex acts is experimental evidence for networks that can be tuned to accomplish different goals, and even to accomplish the same goal by subtle changes in the tuning (e.g., the single reaching goal, initiated from different positions [ 118 ]: “…after approximately 30 years of studies on the reference frame’s representation for hand position and movement in the cerebral cortex, experimental evidences and theoretical studies favor the existence of multiple, simultaneous representations of reach plans in different, dynamic (that is evolving during the task), hybrid, and task-dependent representations”: see also [ 121 ].

To argue for performance across a continuum of tasks, ranging from oromotor, nonverbal tasks to speech performance does not invalidate a task-dependency perspective on oromotor control. As in motor control of the limbs, hand, and eyes, and in postural control, motor speech production requires a network that includes attention to a goal, to the meaning of its task. The task in speech motor control is to enact phonetic sequences via the speech acoustic signal, which along with sensorimotor information originating in receptors in oromotor tissues, are integral to the tuning of networks serving speech motor control. By definition, oromotor nonverbal tasks are performed without access to the speech signal, as well as somatosensory information derived from air flows and pressures that are modulated by opening and closing valves (e.g., at the larynx, velopharyngeal port, and different locations along the vocal tract).

As described by Hickok [ 128 ], the dual-stream model of language processing includes an “auditory-motor” zone in the brain that coordinates the transition between speech perception and motor control for speech as well as simpler forms of vocalization such as humming. The humming example, according to Hickok, shows that activation of the zone is not “speech-specific”. However, it is specific to the generation of sound by the vocal tract (as in the case of humming). Activity in the zone is also “motor-effective selective”, responding more to covert humming when compared to keyboard reproduction of simple melodies (Ref. [ 128 ], p. 61). The auditory-motor zone is not separate from speech motor control processes, rather it is essential to the processing of receptive and expressive language. When an oromotor task does not require the integration of auditory and motor information, it is not speech. Within the speech motor control network, and in other motor control networks, subtle differences in activity weights can account for variations in language behaviors, including speech production. Within the auditory-motor zone, the balance of activity between auditory versus motor neurons can be tuned [ 128 ] to adjustments in speech behaviors. Such shades of tuning can be hypothesized for modifications of speaking rate, clarity, accent simulation, imitation, and other variations of speech production skills, including speech production acts that are not tied to meaning, such as diadochokinesis (DDK). The notion of task specificity in oromotor control, especially in the debate concerning the relevance of oromotor nonspeech behaviors to speech motor control, does not require, as Maas [ 26 ] argues, qualitatively different, special control mechanisms for every variation in how speech is produced.

Ultimately, the most powerful persuasion in this debate is vested in relevant data. The next section presents, in condensed form, results from studies in which relationships between performance on oromotor nonspeech tasks and measures of speech production were explored.

6. Empirical Findings

6.1. selection, organization, and interpretation of evidence.

This section presents a summary of selected representative results, primarily published in the last twenty years, of relationships between performance on oromotor, nonspeech tasks and measures of speech production, speech acoustics, and of perceptual variables such as scaled severity of speech impairment and speech intelligibility. Some studies explored relationships between two or more oromotor nonverbal measures, or between oromotor nonverbal and speech production measures only in neurologically healthy individuals; these are listed in Table 1 . Speakers in the studies listed in Table 2 are primarily people with dysarthria, but a few studies of speakers with apraxia of speech are summarized as well, including both children and adults. Several studies published prior to Weismer [ 6 ] are included in the current summary, but those reported in Tables II and III of Weismer (p. 325; 330) are not repeated here.

A comment is in order on the strategy for selecting articles summarized in Table 1 and Table 2 . Searches of relevant databases (e.g., PubMed, Science Direct, Google Scholar) and citations in recent reviews of oromotor performance and its relationship with speech production guided selection of publications included here. “Selection” is perhaps not a precise term, as my aim was to include all relevant publications, primarily from the last two decades. The term “selection” is used to acknowledge the possibility of failing to identify relevant publications.The search strategy was not constrained by the outcome of a publication. No claim is made that these searches adhered to the rules of systematic reviews.

The findings of studies listed in Table 1 and Table 2 were evaluated with the qualitative approach used in [ 6 ]. The fourth columns in both tables are headed “Overall Findings”, which are judged for each publication to be “Positive”, “Mixed” or “Negative”. “Positive” denotes a study in which a significant relationship (or more than one) was found between oromotor, nonspeech performance and speech production and or speech intelligibility measures. “Mixed” indicates studies in which some relationships were significant, others nonsignificant. A judgment of “Negative” was made for studies in which no significant relationships were found, or, when multiple comparisons were made and the vast majority were nonsignificant. Because of the different conditions, participants, measures of both nonspeech and speech, and type of experiment across the group of studies listed in Table 1 and Table 2 , many different groupings can be imagined for presentation of the reviewed studies. I chose to group the studies by their qualitative summary as explained immediately above. Within each subgroup (i.e., Positive, Mixed, and Negative) studies are listed alphabetically.

The judgments of overall findings in Table 1 and Table 2 are subjective. I have tried to offset confirmation bias by conservative assignment of overall findings, especially in the case of “mixed” judgments. The tables are meant as a guide; different opinions may be formed than the ones given here.

Also available are several systematic and narrative reviews of studies relevant to the oromotor nonverbal/speech production debate. These are summarized first, followed by studies including only neurologically healthy people ( Table 1 ). This section is concluded with the data from studies in which the participants were either persons with neurologically based speech disorders, or persons representing both neurologically healthy and neurologically based speech disorders ( Table 2 ).

6.2. Published Reviews

A small number of narrative, scoping, and systematic reviews are available concerning the role of oromotor nonspeech performance in understanding both typical and disordered speech motor control. Ref. [ 129 ] reviewed the imaging and behavioral data concerning temporal control for speech production and nonspeech (e.g., finger tapping), and concluded that speech timing is a composite of speech-specific and general “clock” mechanisms. This review is relevant to questions of how rhythm and rate in speech production might be modeled by oromotor nonverbal tasks (e.g., Ref. [ 35 ]). Refs. [ 16 , 18 , 20 , 130 , 131 ] reviewed the use of NSOM tasks in treating speech sound (phonological) disorders in children, and their role in speech development. All of these reviews note the lack, even absence of, evidence for the effectiveness of oromotor nonverbal tasks in speech development and speech sound disorders. Lass and Pannbacker (Ref. [ 130 ], p. 408) concluded their review by stating that, “OMEs should ‘be excluded from use as a mainstream treatment until there are further data”. The systematic review by [ 20 ] of the role of oromotor exercises in the treatment of speech disorders identified eight articles that met the strict criteria for inclusion; none provided compelling evidence for the efficacy or effectiveness of these techniques. McCauley et al. (Ref. [ 20 ], p. 353) take a conservative view of their analysis: “The conclusion that must be drawn from this review is the existing research literature provides insufficient evidence to support or refute the use of nonspeech OMEs”. Thus, Lass and Pannbacker, and McCauley et al., both identify the absence of positive evidence, but reach different conclusions about how to interpret the findings. Kent [ 25 ] (p. 774), based on a narrative review, judges the existing evidence for a role of oromotor nonverbal performance in the understanding of typical and disordered speech motor control as “equivocal”: “Wholesale rejection of these methods seems imprudent, given their inclusion in apparently useful and efficacious assessments and interventions”.

In the present opinion, within the larger context of empirical findings prior to publication of [ 20 , 25 ] and the theoretical issues discussed above, the conclusion reached by Lass and Pannbacker [ 130 ] does not seem imprudent. Rather, the conclusion reflects a more prudent outlook on the available data than expressed by [ 20 , 25 ]. Negative effects do not always point to the need for more research or continued use in a therapeutic setting. The question can be asked, if oromotor, nonverbal performance seems so naturally relevant to typical and disordered speech motor control, why has it been so difficult to demonstrate that relevance experimentally, and in the clinic?

Summary of studies of the relationships between oromotor nonverbal performance and measures of speech production in healthy individuals.

Authors/Date	Population	Tasks	Overall Findings	Comments
Chang, Kenney, Loucks, Polleto, Ludlow (2009) [ ]	Healthy adults	Neural substrates of speech (e.g., /saip-kuf/) and non-speech gestures (e.g., kiss snort) (fMRI methods)	Positive	Activity regions for nonlexical, phonotactically legal “word” pairs overlap with pairs of oromotor behaviors
Tremblay & Gracco (2010) [ ]	Healthy, right-handed adults	Comparison of neural substrates for volitional vs. stimulus-driven response selection for words and oral motor gestures	Positive	Largely overlapping neural network for selection of words and oral gestures
Tremblay & Gracco (2009) [ ]	Healthy, right-handed adults	Repetitive transcranial magnetic stimulation (rTMS) used to interfere with pre-SMA during selection of words and oral gestures	Positive	rTMS had similar impact on volitional planning of words and oral gestures
Lancheros, Jouen, Laganaro (2020) [ ]	Healthy adults	Investigated dynamics of motor planning for nonspeech gestures matched to monosyllabic words and nonwords (EEG, ERP methods)	Mixed	Production of speech and nonspeech gestures recruited the same neural networks but the dynamics were distinct for speech and nonspeech
Stipancic, Kuo, Miller, Ventresca, Sternad, Kimberley, Green (2021) [ ]	Healthy youngadults	Evaluated effects of periods of continuous chewing and speech on speech motor learning (8-syllable nonwords)	Mixed	Continuous chewing facilitated subsequent speech performance, but periods of continuous speech impeded subsequent speech performance
Arnold, MacPherson, Smith (2014) [ ]	Healthy children (7–9 years) and young adults	Autonomic arousal associated with speech and nonspeech tasks	Negative	Speech tasks elicit greater autonomic arousal than nonspeech. Children and adults had similar autonomic arousal for speech tasks but children had higher arousal for nonspeech tasks than adults
Bilodeau-Mercure P. Tremblay (2016) [ ]	Healthy young (18–39 years) and older (66–85 years) adults	Lip and tongue muscular strength, endurance, and sensitivity compared to speech rate and accuracy of syllable sequences	Negative	Only muscular endurance of lips associated with age-related changes in speech
Bonilha, Moser, Rorden, Baylis, Frideriksson (2006) [ ]	Young healthy, right-handed adults	Functional magnetic resonance imaging (fMRI) during speech and non-speech movements	Negative	Speech recruited left inferior frontal gyrus, but not the insula; insular activation not observed when speech contrasted with non-speech
Poletto, Verdun, Strominger, Ludlow (2004) [ ]	Healthy adults	Compared laryngeal vocal fold movement and muscle activity during speech (sylla-ble production) and nonspeech gestures (sniff, cough, throat clear)	Negative	Found different combinations of muscle activation for tasks related to respiration, airway protection, and speech
Simione, Fregni, Green (2018) [ ]	Healthy adults	Applied transcranial direct current stimulation (tDCS) to jaw movements associated with speech, maximum syllable repetition, and chewing	Negative	tDCS effects are task dependent
Tremblay, Houle, Ostry (2008) [ ]	Healthy adults	Examined transfer of learning on pairs of utterances matched on kinematic features	Negative	Speech learning failed to transfer to utterances with movements similar to those of trained utterances
Tremblay, Shiller, Ostry (2003) [ ]	Healthy adults	Mechanical (somatosensory) perturbation of jaw during speech, ‘silent speech,’ and non-speech jaw movement	Negative	Adaptation of jaw movement to force perturbation for speech but not nonspeech

6.3. Studies of Oromotor, Nonverbal Measures and Speech Performance in Healthy Individuals

6.3.1. positive findings.

The twelve studies listed in Table 1 differ widely in experimental questions and methods. Three of the studies [ 10 , 132 , 133 ] were judged to have positive results. Using fMRI, the authors of a previous study [ 132 ] observed overlapping areas of activity for non-lexical, phonotactically legal consonant-vowel-consonant (CVC) pairs (English) and pairs of non-speech sounds such as “kiss-snort” and “cough-sigh”. The non-speech gestures activated a wider range of neural tissue compared to the CVCs, but the extent of common activation areas for the two types of gesture led the authors of [ 132 ] to argue for shared mechanisms of vocal tract control in speech and oromotor nonspeech production. The authors of [ 10 , 133 ], using repetitive transcranial magnetic stimulation (rTMS) and fMRI, compared the neural mechanisms of response selection for speech (monosyllabic words) and oromotor nonverbal tasks (e.g., growling, kiss). Tremblay and Gracco argued that the results of the two studies suggest similar oromotor control for speech and nonspeech vocal tract sounds. In a general sense, their results and interpretation are consistent with [ 132 ], but the former work [ 10 , 133 ] was concerned with the commonalities of response selection mechanisms for the selection of speech versus oromotor nonspeech production, the latter [ 132 ] presumably with the overlapping topology of activity areas in the brain for speech and nonspeech sounds.

6.3.2. Mixed Findings

The results of [ 135 ] ( Table 1 ) were judged to be mixed. There was a positive effect of chewing gum for ten minutes on a subsequent, challenging speech motor learning task. Conversely, a ten-minute period of continuous speech resulted in negative speech motor learning relative to a control condition. The cortical silent period, the interruption of an EMG signal following TMS stimulation of a target location on the primary motor cortex, was not significantly different for lip electrodes across the continuous chewing and speaking tasks. The worse-than-baseline effect of continuous speaking, plus the absence of an electrophysiological effect, were judged to be negative results for the effect of chewing on speech production behavior. The interpretation of this study is complicated by the potentially variable effects of memory on the outcome and the counterintuitive difference between the chewing and speech conditions. Results from [ 134 ], an EEG/ERP study of nonspeech gestures, nonsense words and words, were judged as mixed due to findings of similar planning processes, but differing dynamics (the temporal evolution of ERPs) between nonspeech and speech tasks. The authors suggest these results are not consistent with the TDM but admit that the differing dynamics of the tasks—especially between nonspeech and speech—suggest modifications of the common processes as oromotor control nears the execution stage. Lancheros et al. seem to view the IM as linked inextricably with the “special mechanism” issue discussed in Section 4.1 . Their notion of explaining the differing dynamics of a common network is very much like the idea of adjustable networks—not special mechanisms—in the service of differing action goals [ 118 , 143 ]. As noted above, special, dedicated mechanisms for speech production are not required in the TDM.

6.3.3. Negative Findings

The remaining seven studies in Table 1 reported comparisons in which the negative outcomes favor a TDM-type model. Ref. [ 137 ] reported the effect of different oromotor, nonverbal tasks of the lips and tongue on rate and segmental errors in rapid syllable repetition across neurologically healthy groups of younger and older speakers. Among several oromotor, nonspeech behaviors such as lip and tongue strength, endurance, and tactile sensitivity, only muscular endurance of the lips was associated with age-related changes in speech. Using electromyographic recordings of laryngeal muscles [ 139 ], the authors investigated task-specific patterns of muscle activity for vocal fold vibration, cough, sniff, and rapid shifts between vocal fold opening and closing. According to the authors, their findings, “…limit the ability to use the same biomechanical models of muscle activity to predict movement across tasks” (p. 865). Ref. [ 136 ] found autonomic arousal in adults to be greater for speech compared to nonspeech behaviors, likely a result of the cognitive-linguistic nature of speech production compared to oromotor, nonspeech behaviors. A study of jaw kinematics under the influence of tDCS showed different effects in a speech task (sentence production) versus an oromotor, nonverbal task (chewing), suggesting task specificity for speech motor control [ 140 ]. In another study of speech jaw movements, participants learned nonsense utterances that had been paired with new (not learned) utterances constructed with expected movements similar to those trained. Transfer of learning of the trained movements to these new utterances did not occur (“speech learning is extremely local and incompatible with the notion that speech motor function involves a generalized dynamics representation” (Ref. [ 141 ], p. 2426). A similar study of movement corrections measured during jaw movement in response to force perturbations in a protrusive direction analyzed effects during overt, silent speech, and nonspeech gestures across conditions; similar corrections of jaw movement were observed for the overt and silent speech conditions, which differed from the nonspeech condition (Ref. [ 142 ], Figure 2, p. 886). Both Tremblay et al. studies involved a single articulator, which restricts the scope of interpretation. Finally, an imaging study showed significantly different regions of brain activity for speech versus nonspeech behavior (Ref. [ 138 ] in contrast to the findings of [ 132 ]).

The judgments above of study results in which speech and nonspeech behavioral, imaging, and electrophysiological analyses are compared and found to be different across tasks can be considered along with empirical data for neurologically healthy participants summarized previously by Weismer (Ref. [ 6 ] Table II). As noted above, the negative judgments were made when there was a difference between the speech and nonspeech tasks. The weight of the evidence for neurologically healthy individuals favors task specificity of speech motor control.

Summary of studies of the relationships between oromotor nonverbal performance and measures of speech production in neurologically based speech disorders.

Authors/Date	Population	Tasks	Overall Findings	Comments
Berggren, Hung, Dixon, Bounsanga, Crockett, Foye, Gu, Campbell, Butterfield, Johnson (2018) [ ]	Children with congenital myotonic dystrophy and healthy controls	Maximum anterior tongue pressure and lip strength, ratings of dysarthria	Positive	Moderate correlation of strength measures with dysarthria ratings
Jones, Crisp, Asrani, Sloane, Kishnani Kishnani (2015) [ ]	Late-onset Pompe Disease	Quantitative analysis of lingual strength and speech intelligibility; judgments of dysarthria severity	Positive	As dysarthria increased, lingual strength decreased
Puyjarinet, Bégel, Gény, Driss, Cuartero, Kotz, Pinto, Dalla Bella (2019) [ ]	Adults with Parkinson’s Disease	Compared orofacial (DDK, pseudoword), manual, and gait tasks	Positive	Reported general rhythmic impairment across structures
Bose & van Lieshout (2012) [ ]	Adults with aphasia and healthy controls	Lip movement for speech-like and non-speech tasks (kinematic/coordination indices)	Mixed	No difference between bilabial closure kinematics for non-speech and bilabial DDK sequences, except at fast rates
Clark, Duffy, Strand, Hanley, Solomon (2022) [ ]	Flaccid, spastic, mixed spastic–flaccid, ataxic, or hypokinetic dysarthria types and healthy controls	Compared orofacial muscle strength (tongue, lips, cheeks) across types of dysarthria and dysarthria severity	Mixed	Maximum strength and severity of dysarthria poorly correlated; Explains no more than 20% of variance across all speakers with dysarthria
Searl, Knollhoff, Barohn (2017) [ ]	People with amyotrophic lateral sclerosis (ALS) and healthy adults	Lingual-alveolar contact pressure during speech; speech intelligibility	Mixed	Some measures correlated with word intelligibility; no significant group difference in %Max; varying bulbar severity may explain significant results
Tamura, Tanaka, Watanabe, Sato (2022) [ ]	Patients with dysarthria and healthy adults	Maximum tongue pressure and speech intelligibility, DDK, second formant slope	Mixed	Maximum tongue pressure correlated significantly with F2 slope in males, not in females; No significant correlations between the maximum pressure and intelligibility or DDK rate
Whiteside, Dyson, Cowell, Varley (2015) [ ]	Acquired apraxia of speech (AOS) and oral apraxia (OA)	Compared speech and volitional nonspeech oral movements	Mixed	Moderate association between AOS and OA but also evidence of double dissociation
Chu, Barlow, Lee (2015) [ ]	Adults with Parkinson’s Disease and healthy controls	Perioral stiffness, labial movement amplitude, electromyographic activity during syllable production	Negative	No significant correlation between upper- or lower-lip stiffness with labial kinematics except for UL at fast rate
Dietsch, Solomon, Sharkey, Duffy, Strand, Clark (2014) [ ]	Flaccid, flaccid-spastic, ataxic, hypokinetic, or spastic dysarthria and healthy controls	Perceptual and instrumental measures of orofacial muscle tone and different types of dysarthria; 3 studies	Negative	Negative in people with dysarthria; No clear relationship between dysarthria type and orofacial muscle stiffness
Mackenzie, Muir, Allen, Jensen (2014) [ ]	Adults with post-stroke dysarthria	Randomized feasibility trial comparing speech practice alone to speech plus NSOM exercises	Negative	No difference in behavioral intervention outcomes
Neel, Palmer, Sprouls, Morrison (2015) [ ]	Adults with oculopharyngeal muscular dystrophy and healthy controls	Articulatory tasks, tongue strength, speech-like tasks, perceptual speech ratings	Negative	Nonspeech tasks did not predict speech measures
Potter, Nievergelt, VanDam (2019) [ ]	Children and adolescents with typical development, speech sound disorders (SD), motor speech disorders (MSD)	Tongue strength (IOPI) compared to severity of speech sound disorder	Negative	Tongue strength not related to severity of speech sound deficits in SD or MSD
Schölderle, Staiger, Ziegler (2018) [ ]	Adults with cerebral palsy and concomitant cognitive impairment	Feasibility of speech and non-speech tasks in diagnosis of dysarthria	Negative	Speech tasks more feasible (no ‘dysexecutive’ behavior) relative to non-speech tasks
Solomon, Makashay, Helou, Clark (2017) [ ]	Adults with dysarthria and healthy matched controls	Orofacial strength measures compared to speech intelligibility, articulation rate, fast-syllable repetition	Negative	“Tenuous links between orofacial strength and speech production disorder”
Staiger, Schölderle, Brendel, Bötzel, Ziegler (2017) [ ]	Patients with neurogenic movement disorders (Parkinson’s disease, stroke, cerebral palsy, primary dystonia, progressive supranuclear palsy; cerebellar ataxia) and healthy controls	Rate data were compared for speech (oral reading), speech-like (rapid syllable repetition), and nonspeech (rapid single articulator) movements Factor analytic approach used to compare types of tasks	Negative	Factor analysis revealed that rate performance on different types of tasks loaded onto separate latent variables
Staiger, Schölderle, Brendel, Ziegler (2017) [ ]	Patients with neurogenic movement disorders (Parkinson’s disease, stroke, cerebral palsy, primary dystonia, progressive supranuclear palsy; cerebellar ataxia) and healthy controls	Rate data were compared for speech (oral reading), speech-like (rapid syllable repetition), and nonspeech (rapid single articulator) movements Multiple single-case methods used to test differences between three tasks for individual patients	Negative	Statistically significant dissociations between rates on speech tasks and those from speech-like or nonspeech tasks for a number of patients
Wood, Hughes, Hayes, Wolf (1992) [ ]	Patients with Parkinson’s disease, stroke, multiple sclerosis and healthy controls	Comparison of quantitative measures of lip force and clinical judgment of the presence of a motor speech disorder	Negative	Dissociation between force measures and presence vs. absence of dysarthria
Ziegler, Schölderle, Brendel, Risch, Felber, Ott, Goldenberg, Vogel, Bötzel, Zettl et al. (2023) [ ]	Persons with dysarthria (PWD; 6 etiologies) and healthy controls	Evaluation of how a battery of nonspeech parameters relate to speech characteristics in PWD; 23 different diagnostic measures assessed	Negative	Standard orofacial motor tasks failed to characterize speech characteristics of PWD; Found lack of overlap between speech and nonspeech domains

6.4. Studies of Oromotor, Nonverbal Measures and Speech Performance in Individuals with Motor Speech Disorders and Other Selected Speech Disorders

Table 2 lists 19 studies in which comparisons were made between oromotor, nonverbal and speech tasks, for speakers with motor speech disorders and other selected speech and/or language disorders. The vast majority of these papers included speakers with dysarthria; a few studies reported data on speakers with aphasia, acquired apraxia of speech, and children with speech sound disorders.

6.4.1. Positive Findings

Three studies were judged to show positive results for a relationship between oromotor nonverbal behavior and perceptual measures of dysarthria in children with congenital myotonic dystrophy and late-onset Pompe disease [ 144 , 145 ]. Anterior tongue strength was measured in Berggren et al. [ 144 ] using the Iowa Oral Performance Instrument (IOPI), a widely used device used to measure maximum anterior tongue pressures, and a force meter to measure lip strength via resistance of the lips to horizontal stretch. Dysarthria—presumably meaning, “severity”—was measured on a 4-point, rank order scale with numbers attached to descriptors such as “100% intelligible” and “reduced intelligibility”. It is not clear who made the number assignments on the intelligibility scale, or the reliability of the perceptual judgments. Berggren et al. (Ref. [ 144 ], p. 415) report, “The presence of any dysarthria showed a moderate negative correlation with IOPI performance…”. The significant correlation was −0.538: lower maximum tongue pressures were associated with higher numbers on the dysarthria scale. [ 145 ] reported a relationship between lingual strength and dysarthria severity in adults with late-onset Pompe disease. The statistical basis of this relationship is not correlative, but rather an observation that participants with greater tongue strength tended to have less severe dysarthria. The third positive results are from a study of persons with Parkinson’s disease [ 146 ], in which similar rhythmic variability was found across participants for three motor behaviors—gait, tapping, and DDK (rapid repetitions of /pʌtʌkʌ/). These findings were interpreted by the authors as a reflection of a domain-general timing mechanism. This positive evaluation is based on the absence of a clear dissociation between rhythmic control in speech and other motor behaviors.

6.4.2. Mixed Findings

Five studies in Table 2 were judged to have mixed results, among which are four [ 42 , 47 , 147 , 148 ] concerning relationships between speech production tasks and oromotor, nonverbal measures of strength, tone, and movement. Ref. [ 42 ] obtained maximum strength measures for the lips, tongue, and cheeks for speakers with one of five types of dysarthria as reported in Table 2 . The maximum strength measures distinguished some dysarthria groups from others, but the statistical effects depended on oromotor task (e.g., tongue protrusion, cheek compression, lip compression) and dysarthria type. Orofacial maximum strength measures were weakly correlated with perceptual estimates of dysarthria severity, at best explaining 20% of the variance between the measures. The judgment of mixed results is based on some discrimination of dysarthria type by maximum strength, but poor prediction by the latter measures of dysarthria severity. In a study of intercorrelations among measures of maximum tongue pressure, DDK rate, F2 slope for Japanese diphthongs and glides, and speech intelligibility in a group of speakers with dysarthria, only F2 slope in male participants was correlated significantly (r = 0.397) with the maximum strength values [ 47 ]. When the data were broken down by dysarthria type, the significant maximum pressure-F2 slope correlations were detected for speakers with flaccid dysarthria (r = 0.786) and mixed dysarthria (0.640). Examination of Figure 3 in [ 47 ] suggests a disproportionate role of severity in these statistical relationships. Ref. [ 148 ] related speech accuracy scores to nonspeech oral movements in adult speakers diagnosed with acquired AOS and found a significant but weak correlation (0.395) between the variables (see their Figure 1). A study of speakers with ALS and control speakers [ 147 ] reported significant correlations between single word intelligibility scores and both the maximum anterior-tongue nonspeech pressures and contact pressures measured for lingual-alveolar consonants during speech production. These positive results are offset by the extensive overlap of speech task contact pressures, for some phonemes, between control speakers and speakers with ALS. In other words, between-group intelligibility differences seemed to be associated with similar contact pressures for some phonemes. Of great interest are the low-contact pressure values for lingual-alveolar consonants relative to maximum anterior tongue pressures for speakers in both groups [ 147 ]. This finding raises important concerns about the value of information provided by measurements of maximum tongue pressure, and similar maximum efforts in articulators such as the jaw and lips. Ref. [ 31 ] performed a study in which action goals of a string of nonspeech vocal tract gestures were matched to the goals of repeated syllable sequences (/pa/); the goal for both sequences was lip closure, and the two gesture sequences were produced at normal and fast rates by neurologically healthy controls and speakers with aphasia. Lip closure gestures were indexed by labial kinematic measures of amplitude, duration, peak velocity, and several derived measures of coordination. The statistical results showed no effect for Groups (controls vs. aphasic individuals) and a single main effect for LL duration for the difference between speech and nonspeech gestures. Significant Interactions between the main effects and rate were most prominent, with greater differences between DDK and sequential lip closure gestures at the fast rate. The judgment of mixed results is based on the similarity of lip closure kinematics—the absence of main effects for speech versus nonspeech gestures—but significant interactions between the gesture types and rate (see Table 2 ).

6.4.3. Negative Findings

The eleven studies listed in Table 2 with a negative judgment include nine with straightforward summary statements. Speakers with PD showed non-significant correlations between a measure of lip stiffness and labial kinematic measures [ 149 ]. Small and/or nonsignificant correlations between orofacial maximum force measures and measures of speech production, or perceptual estimates of severity or speech intelligibility, were reported for dysarthric adults with oculopharyngeal muscular dystrophy [ 150 ] for children with motor speech disorders, as well as with motor speech disorders secondary to Galactosemia [ 151 ], for adults with various types of dysarthria [ 152 ], and for speakers with PD [ 153 ]. Using instrumental measures, ref. [ 43 ] failed to find a relationship between instrument-based and perceptual measures of orofacial muscle tone and severity of dysarthria in groups of persons with the same dysarthria types as in [ 42 ]. In a series of studies [ 7 , 21 , 34 ] performance by speakers with dysarthria on oromotor nonverbal tasks of the type frequently administered in the clinic were grouped statistically in a different category compared with speech measures. In a related study [ 27 ], verbal speakers with cerebral palsy were significantly less likely to complete nonspeech (including rapid syllable repetition) than speech tasks (see also [ 112 ]; the opposite pattern—participants being less likely to complete speech but not nonspeech tasks—was rare. Finally, a randomized trial of speech improvement in adults with post-stroke dysarthria compared treatment outcomes between two groups, one of which received speech practice, the other speech practice plus oromotor nonverbal exercises; treatment outcome measures for the two groups were equivalent [ 19 ].

7. A Note on DDK

Kent, Kim, and Chen [ 13 ] recently reviewed the substantial literature on DDK up to the time of their publication. Four notable and worthy features of this paper deserve mention. First, the tabled citations and data are an invaluable resource for future scholarship. Second, separate sections are devoted to different disorders, and most importantly for the current essay, there is a carefully considered section on motor speech disorders (Ref. [ 13 ], pp. 597–604). Third, a graph is presented in Table 1 (p. 579) showing the yearly number of publications since 1990 in which DDK was studied or reviewed. In 2010, the number of relevant publications per year began to increase dramatically, reaching a peak of 46 publications in both 2020 and 2021. An educated guess projects a continuation of the trend for increasing publication on DDK in a variety of speech disorders, and especially in motor speech disorders. Fourth, most, if not all of the information in the section on motor speech disorders (and other sections) is concerned with DDK as a means to diagnose disease and/or dysarthria type, or childhood apraxia of speech or acquired apraxia of speech in adults, rather than identify specifics of speech production and their potential effects on speech intelligibility.

To the best of my knowledge, only a few studies have addressed the question of how DDK analyses inform knowledge of variables such as vowel and consonant precision, types of segmental or syllabic errors, even rhythmic characteristics of speech in the service of communication. Interestingly, two studies cited by [ 13 ], and earlier by [ 6 ], were concerned with the relationship between performance in a variety of NSOM tasks and segmental production in DDK strings. In his study of oromotor nonverbal performance by speakers with cerebral palsy and dysarthria, Schliesser [ 111 ] examined NSOM tasks that in theory might be linked statistically with segmental properties in the DDK strings, such as consonant place of articulation. This result was not confirmed by the expectation: “only one of the 15 intercorrelations possible between speech and nonspeech alternate motion rates seems noteworthy, repeating /gʌ/ with retraction and rounding of the lips” (Ref. [ 111 ], p. 262). A similar disconnect between oromotor performance and segmental production was noted in [ 112 ], and the authors observed that maximum rate of nonverbal lip contraction was not more highly correlated with the maximum rate of /pʌ/ repetitions compared with /tʌ/ repetitions, nor was the maximum rate of tongue contraction more highly correlated with the maximum rate of /tʌ/ repetitions compared with /pʌ/ repetitions. Analyses extended to possible implications of DDK characteristics (rate, variation of rate, precision of consonants and vowels) for segmental and/or suprasegmental characteristic of speech production would be helpful.

Measures derived from DDK performance may be used to track articulatory changes over time in persons with progressive neurological disease and dysarthria [ 104 ], or as a kind of stress test for oromotor integrity [ 154 ]. However, it is also possible that other measures, such as speaking rate derived from sentence production, can do the same with empirically derived limits for clinically important changes [ 155 ]. In a recent study [ 156 ], five acoustic measures derived from a sequential motion rate task, each measure hypothesized to correspond to a specific articulatory characteristic (e.g., F2 slope reflecting speed of articulatory movement; across repetition variability of VOT reflecting stability of speech sounds across repetitions) showed that taken together the measures classified five neurological disease types with “good to excellent” accuracy. An interesting extension of this work would be to see how these acoustic features mapped on to the same measures in connected speech samples.

DDK is a staple in our field but remains mysterious with respect to prediction of speech characteristics important to questions of speech intelligibility specifically, and communication ability generally. Apart from an index of severity, there is not a lot of evidence that it is useful for more specific observations. The opinion offered by [ 21 ] regarding the utility of DDK in clinical settings where people with motor speech disorders are diagnosed and treated seems correct until proven otherwise. The original recordings that served as the basis for the Mayo Clinic classification of dysarthrias provide a cautionary tale about the relationship between DDK and spontaneous speech. Each participant in the database produced several different speech samples, including DDK for stop-consonant-vowel syllables, as well as a spontaneous speech sample in conversation with the examiner. In these recordings, there are many examples of poor DDK performance within individuals, not only for rate but for rhythm and consonant precision, which nevertheless is associated with intelligible or minimally unintelligible speech during the spontaneous samples).

8. Overall Summary

SLPs and SLTs make frequent use of NSOM tasks, as do scientists who conduct research on speech production and its disorders. Yet a coherent theoretical treatment of, and rationale for, a meaningful relationship between the two have not been formulated and remain under spirited debate. A significant piece of the debate is the acceptance or rejection of the concept of task specificity, in which motor control processes depend on the goal of the action under control. Analysis of the structure and opposed predictions of two much-discussed “models” of oromotor control in nonspeech and speech motor control, the IM and TDM, were presented. The IM is critical of task specificity as a guiding principle in the study of speech motor control; the TDM embraces it. Information from the literature on limb and hand motor control, and on rehabilitation strategies to improve control in persons affected by acquired brain damage, was brought in to show how task specificity is a well-accepted and preferred concept in which goals are not separable from other motor processes. A critical distinction was made between NSOM tasks as a means to diagnose the type of neurological disease, compared with the prediction of speech production deficits likely to result in varying degrees of intelligibility loss, or intelligible speech production that calls attention to itself when listeners hear something different from “typical” speech patterns. Experimental results addressing the relationship were tabulated and analyzed, leading to the conclusion that there is little evidence for insights to specific characteristics of speech motor control deficits provided by oromotor nonverbal motor control tasks. The latter may have some use in diagnosing the neurological diseases responsible for a speech motor control deficit. However, the value of such information in identifying the speech movement and acoustic underpinnings of dysarthria in its many expressions has yet to be demonstrated. To move the research and clinical disciplines of speech motor control forward, the study of speech production and its goal of providing listeners with time-varying, linguistically relevant acoustic signals, is necessary and (I believe) sufficient.

Acknowledgments

The author thanks Susan Ellis Weismer for her contributions to every aspect of this project, and more.

Funding Statement

This research received no external funding.

Conflicts of Interest

The author declares no conflict of interest.

Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

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Second Language Speech Learning

Second Language Speech Learning

Theoretical and empirical progress.

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Including contributions from a team of world-renowned international scholars, this volume is a state-of-the-art survey of second language speech research, showcasing new empirical studies alongside critical reviews of existing influential speech learning models. It presents a revised version of Flege's Speech Learning Model (SLM-r) for the first time, an update on a cornerstone of second language research. Chapters are grouped into five thematic areas: theoretical progress, segmental acquisition, acquiring suprasegmental features, accentedness and acoustic features, and cognitive and psychological variables. Every chapter provides new empirical evidence, offering new insights as well as challenges on aspects of the second language speech acquisition process. Comprehensive in its coverage, this book summarises the state of current research in second language phonology, and aims to shape and inspire future research in the field. It is an essential resource for academic researchers and students of second language acquisition, applied linguistics and phonetics and phonology.

'Striking a good balance between theoretical arguments and empirical findings, this book offers linguistic perspectives on second language (L2) speech learning, which can inform applied linguistics in L2 speech research.'

Okim Kang - Professor of TESL / Applied Linguistics, North Arizona University

'Containing the revised version of one of the field’s most influential models, a series of empirical studies, and review chapters on a wide variety of topics, and even practical guidelines for L2 speech researchers, this book sets a new landmark in L2 speech research.'

Juli Cebrian - Associate Professor, Universitat Autònoma de Barcelona

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Second Language Speech Learning pp i-ii

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Second Language Speech Learning - Title page pp iii-iii

Theoretical and Empirical Progress

Copyright page pp iv-iv

Dedication pp v-vi, contents pp vii-ix, figures pp x-xv, tables pp xvi-xvii, contributors pp xviii-xxii, preface pp xxiii-xxvi, acknowledgments pp xxvii-xxviii, part i - theoretical progress pp 1-192, chapter 1 - the revised speech learning model (slm-r) pp 3-83.

By James Emil Flege , Ocke-Schwen Bohn

Chapter 2 - The Revised Speech Learning Model (SLM-r) Applied pp 84-118

By James Emil Flege , Katsura Aoyama , Ocke-Schwen Bohn

Chapter 3 - New Methods for Second Language (L2) Speech Research pp 119-156

By James Emil Flege

Chapter 4 - Phonetic and Phonological Influences on the Discrimination of Non-native Phones pp 157-174

By Michael D. Tyler

Chapter 5 - The Past, Present, and Future of Lexical Stress in Second Language Speech Production and Perception pp 175-192

By Annie Tremblay

Part II - Segmental Acquisition pp 193-246

Chapter 6 - english obstruent perception by native mandarin, korean, and english speakers pp 195-212.

By Yen-Chen Hao , Kenneth de Jong

Chapter 7 - Changes in the First Year of Immersion pp 213-227

An Acoustic Analysis of /s/ Produced by Japanese Adults and Children
By Katsura Aoyama

Chapter 8 - Effects of the Postvocalic Nasal on the Perception of American English Vowels by Native Speakers of American English and Japanese pp 228-246

By Takeshi Nozawa , Ratree Wayland

Part III - Acquiring Suprasegmental Features pp 247-334

Chapter 9 - relating production and perception of l2 tone pp 249-272.

By James Kirby , Đinh Lu Giang

Chapter 10 - Production of Mandarin Tones by L1-Spanish Early Learners in a Classroom Setting pp 273-289

By Lucrecia Rallo Fabra , Xialin Liu , Si Chen , Ratree Wayland

Appendix 10.A - Metaphorical Gestures Illustrating the Four Mandarin Tones pp 289-289

Appendix 10.b - speech materials used in the elicitation task pp 289-289, chapter 11 - production of english lexical stress by arabic speakers pp 290-311.

By Wael Zuraiq , Joan A. Sereno

Chapter 12 - Variability in Speaking Rate of Native and Nonnative Speech pp 312-334

By Melissa M. Baese-Berk , Ann R. Bradlow

Part IV - Accentedness and Acoustic Features pp 335-396

Chapter 13 - comparing segmental and prosodic contributions to speech accent pp 337-349.

By Marina Oganyan , Richard Wright , Elizabeth McCullough

Chapter 14 - Do Proficient Mandarin Speakers of English Exhibit an Interlanguage–Speech Intelligibility Benefit When Tested with Complex Sound–Meaning Mapping Tasks? pp 350-376

By Marta Ortega-Llebaria , Claire C. Chu , Carrie Demmans Epp

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Diamond L Mirnig A Fröhlich P (2023) Encouraging Trust in Demand-Side Management via Interaction Design: An Automation Level Based Trust Framework Energies 10.3390/en16052393 16 :5 (2393) Online publication date: 2-Mar-2023 https://doi.org/10.3390/en16052393
Vi C Cornelio P Obrist M Yeomans M (2023) “Sweet: I did it”! Measuring the sense of agency in gustatory interfaces Frontiers in Computer Science 10.3389/fcomp.2023.1128229 5 Online publication date: 12-May-2023 https://doi.org/10.3389/fcomp.2023.1128229
Meck A Sardone M Cullmann J (2023) Will the Assistant Become the Driver, and the Driver Become the Assistant? Proceedings of the 5th International Conference on Conversational User Interfaces 10.1145/3571884.3603753 (1-5) Online publication date: 19-Jul-2023 https://dl.acm.org/doi/10.1145/3571884.3603753
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Meck A Draxler C Vogt T (2023) How May I Interrupt? Linguistic-Driven Design Guidelines for Proactive in-Car Voice Assistants International Journal of Human–Computer Interaction 10.1080/10447318.2023.2266251 (1-15) Online publication date: 15-Oct-2023 https://doi.org/10.1080/10447318.2023.2266251
Cornelio P Haggard P Hornbaek K Georgiou O Bergström J Subramanian S Obrist M (2022) The sense of agency in emerging technologies for human–computer integration: A review Frontiers in Neuroscience 10.3389/fnins.2022.949138 16 Online publication date: 12-Sep-2022 https://doi.org/10.3389/fnins.2022.949138
Stiegemeier D Bringeland S Kraus J Baumann M Ji Y Jeon M (2022) User Experience of In-Vehicle Gesture Interaction: Exploring the Effect of Autonomy and Competence in a Mock-Up Experiment Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications 10.1145/3543174.3546847 (285-296) Online publication date: 17-Sep-2022 https://dl.acm.org/doi/10.1145/3543174.3546847
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Bergström J Knibbe J Pohl H Hornbæk K (2022) Sense of Agency and User Experience: Is There a Link? ACM Transactions on Computer-Human Interaction 10.1145/3490493 29 :4 (1-22) Online publication date: 31-Mar-2022 https://dl.acm.org/doi/10.1145/3490493

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Green human resource management: practices, benefits, and constraints—evidence from the portuguese context.

1. Introduction

1.1. literature review, 1.1.1. concept of green human resource management (ghrm), 1.1.2. ghrm areas, green recruitment and selection, green training and development, green performance management, green compensation and benefits, green organizational culture, 1.1.3. transversal environmental sustainability practices in the literature, 1.1.4. benefits, constraints and challenges of ghrm.

Identify Green Human Resource Management practices in companies operating in Portugal that have environmental management system certification, specifically the ISO 14001 standard.
Identify transversal environmental sustainability practices in companies in Portugal with the ISO 14001 standard.
Identify benefits, constraints, and challenges for companies associated with GHRM from the perspective of their Human Resource Management professionals and those responsible for environmental sustainability.

2.1. Procedures and Sample

2.2. instruments and analysis procedures, 3.1. ghrm practices in portugal, 3.1.1. green recruitment and selection, 3.1.2. green training and development, 3.1.3. green performance management, 3.1.4. green compensation and benefits, 3.1.5. green organizational culture, 3.2. transversal environmental sustainability practices in portugal, 3.3. benefits, constraints, and challenges of ghrm in portugal, 3.3.1. benefits of ghrm in portugal, 3.3.2. constraints of ghrm in portugal, 3.3.3. challenges of ghrm in portugal, 4. discussion, 5. conclusions, 5.1. contributions of the study, 5.2. limitations and further research suggestions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

Interviewee	Interviewee’s Company Sector of Activity Main CAE (CAE-Rev.3)	Nº Workers in Portugal Nº Workers in Portugal Number of Workers in Portugal	Location	Company’s Year Foundation	Interviewee’s Role	Educational Background	Educational Level	Age	Gender	Tenure
I1	Manufacture of chemical products and manufactured fibers, except pharmaceutical products	<1000	Porto	1917	HR Director	Human resources	PhD	41–50	F	1 y 11 m
I2	Financial services activities, except insurance and pension funds	>1000	Lisboa	2000	L&D Coordinator	Engineering	Degree	41–50	F	7 y 10 m
I3	Computer programming and consultancy and related activities	>1000	Lisboa	1967	Sustainability Chief	Environmental engineering	Master	41–50	F	1 y 10 m
I4	Financial services activities, except insurance and pension funds	>1000	Braga	2007	HR Director	Human resources	Master	31–40	M	10 y 5 m
I5	Head office and management consultancy activities	>1000	Lisboa	1999	HR Business Partner	Psychology	Master	31–40	M	1 y
I6	Other consulting, scientific, technical, and similar activities	<1000	Braga	1999	HR Developing manager	Human resources	Degree	31–40	F	21 y 9 m
I7	Waste collection, treatment, and disposal; material recovery	<1000	Porto	2008	HR Director	Geology	Degree	41–50	M	4 y 1 m
I8	Waste collection, treatment, and disposal; material recovery	<250	Porto	1982	HR Chief	Human resources	Degree	41–50	F	21 y 7 m
I9	Postal and courier activities	>1000	Lisboa	2019	HR Director	Human resources	Degree	31–40	M	6 m
I10	Manufacture of electrical equipment	>1000	Porto	1948	Environment, Health and Safety Chief	Human resources	Degree	31–40	F	13 y 7 m
I11	Trade, maintenance and repair of motor vehicles and motorcycles	<1000	Porto/Lisboa/Aveiro	1946	HR Business Partner	Human resources	High School	up to 30	F	5 y 3 m
I12	Manufacture of other non-metallic mineral products	<500	Aveiro	1964	HR Specialist	Sociology	Master	up to 30	F	2 y 10 m
I13	Manufacture of rubber and plastic products	<250	Porto	2006	Developing manager	Environmental management	Degree	41–50	F	1 y 9 m
I14	Financial services activities, except insurance and pension funds	<250	Porto	2008	People and Culture manager	Psychology	Degree	41–50	F	9 y 4 m
I15	Wholesale trade (including agents), except motor vehicles and motorcycles	>1000	Setúbal	1953	HR Director	Human resources	Master	51–60	M	1 y 5 m

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Classification of Adopted Areas	Author(s)	What Comprises This Area	Function Classification	Author(s)
Green recruitment and selection	Renwick et al. [ ]	Job description with environmental dimensions Job advertisements with the company’s environmental values Selection of candidates with a pro-environmental stance and with environmental knowledge to correctly conduct the functions	job design	Arulrajah et al. [ ]
			job analysis	Arulrajah et al. [ ]
			job description and analysis	C. Jabbour et al. [ ]
			human resource planning	Arulrajah et al., C. Jabbour et al. [ , ]
			recruitment	Arulrajah et al., C. Jabbour et al. [ , ]
			selection	Arulrajah et al., C. Jabbour et al. [ , ]
Green training and development	Renwick et al. [ ]	Environmental training programs and good practices	training and development	Arulrajah et al., C. Jabbour et al. [ , ]
Green performance management	Renwick et al. [ ]	Integration of green criteria in evaluations of workers’ professional performance Implement rules of conduct related to ecology and hold workers and managers accountable	performance evaluation	Arulrajah et al. [ ]
			discipline management	Arulrajah et al. [ ]
			performance management	Tang et al. [ ]
			performance appraisal	C. Jabbour et al. [ ]
Green compensation and benefits	Renwick et al. [ ]	Monetary and non-monetary incentives for workers who have achieved environmental goals	reward management	Arulrajah et al. [ ]
Green compensation and benefits	Renwick et al. [ ]		rewarding and compensation	C. Jabbour et al. [ ]
Green organizational culture	adapted from Renwick et al. involvement and empowerment [ ]	Sharing green values between organizations and workers Formal and informal internal communication related to the environment Create green working environments Promote opportunities for worker participation in the environmental strategy, identifying the union and relationship between managers and workers as a key element	socialization	Shahriari and Hassanpoor [ ]
			health and safety management	Arulrajah et al. [ ]
			participation and working relationships	Ahmad and Nisar [ ]
			employee relations	Arulrajah et al. [ ]

Green Recruitment and Selection Practices	Author(s)
Online job description	Deshwal [ ]
Inclusion of the company’s environmental values in job advertisements	Arulrajah et al., Bombiak and Marciniuk-Kluska [ , ]
Reception of online CVs through platforms	Deshwal [ ]
Use of internal job portals that allow access to job application documentation (offer letter, certifications, references)	Deshwal [ ]
Verification of environmental knowledge and skills of candidates in the recruitment process	Bombiak and Marciniuk-Kluska [ ]
Integration of the environmental dimension into the job description of each position, namely the inclusion of ecological skills as transversal skills for all jobs (tasks and responsibilities)	Mehta and Mehta [ ]
Creation of new jobs that dedicate themselves to the organization’s environmental management	Mehta and Mehta [ ]

Green Training and Development Practices	Author(s)
Implementation of environmental management programs to train workers and develop required skills	Arulrajah et al. [ ]
Analysis and individual identification of workers’ ecological training needs	Arulrajah et al. [ ]
Distribution of surveys to workers to determine their level of literacy on the topic	Milliman and Clair [ ]
Holding seminars and workshops to create environmental awareness among workers	Renwick et al. [ ]
Creation of a job rotation system to train environmental issues in practice	Renwick et al. [ ]
Promotion of environmental education among managers and their teams to encourage a change in attitudes and behaviors	Arulrajah et al. [ ]
Organization of competitiveness programs that instill environmental values among workers, involving their families	Saifulina et al. [ ]

Green Performance Management Practices	Author(s)
Development of a disciplinary system that promotes the adoption of environmental conduct	Bombiak and Marciniuk-Kluska [ ]
Preparation of annual surveys measuring the impact of GHRM practices	Mamatha and Bharmappa [ ]
Providing regular feedback to workers on their progress in achieving environmental objectives	Bangwal and Tiwari [ ]
Development of positive reinforcement of environmental management (positive feedback)	Bangwal and Tiwari [ ]
Development of negative reinforcement of environmental management (criticisms, warnings, and suspensions for failures)	Bangwal and Tiwari [ ]
Penalty for non-compliance with environmental management goals	Bombiak and Marciniuk-Kluska, Renwick et al. [ , ]
Inclusion of a topic on environmental skills and know-how in the feedback interview	Opatha [ ]
Assessment of the environmental performance of all workers	Renwick et al. [ ]

Green Compensation and Benefits Practices	Author(s)
Monetary:
Using monetary-based environmental benefits (bonuses, cash, and prizes, such as credit cards to spend on green products)	Renwick et al., Bangwal and Tiwari [ , ]
Non-Monetary:
Personalized offers to reward the achievement of ecological skills (e.g., a free day per quarter for the department that uses less paper)	Bombiak and Marciniuk-Kluska, Gómez et al. [ , ]
Offer of company promotional gifts aligned with the green culture campaign (e.g., lunch boxes, cups)	Gómez et al. [ ]
Use of cash benefits environmental management on a non-monetary basis (special leaves, sabbaticals, gifts)	Renwick et al., Likhitkar and Verma [ , ]
Development of family promotion activities	Gómez et al. [ ]
Use of environmental management benefits based on recognition (awards, advertising, external positions, regular praise, annual dinners with benefits for behavior most exemplary in this field, diplomas of merit)	Renwick et al. [ ]
Benefits for creativity and active participation in green initiatives (career promotions, grants for environmental projects, environmental competitions)	Bombiak and Marciniuk-Kluska, Ari et al. [ , ]
Incentives for the use of bicycles as a means of transport (rented by the company) or use of more ecological (less polluting) vehicles	Saeed et al. [ ]

Green Organizational Culture Practices	Author(s)
Use the knowledge of workers to improve the environmental performance of the company	Siyambalapitiya et al. [ ]
Motivate workers to be green consumers outside organizations through pro-environment labor relations. Examples: encourage recycling at home; buy recycled products; give preference to public transport	Saifulina et al., Jackson et al. [ , ]
Promote green spaces in the company. Example: eco-design	Likhitkar and Verma [ ]
Enable workers to take waste from home to work, inculcating the practice of waste separation and recycling in the home–work–home relationship	Renwick et al. [ ]
Create environmental goals for the company and use communication channels to involve workers in this mission	Bombiak and Marciniuk-Kluska [ ]
Adopt and monitor environmental commitments with suppliers	Gómez et al. [ ]
Define the annual budget for the implementation of environmental initiatives by HRM	Bombiak and Marciniuk-Kluska [ ]
Provide advisory services and support for solving ecological problems	Bombiak and Marciniuk-Kluska [ ]
Prepare sustainability reports annually	Bombiak and Marciniuk-Kluska [ ]
Recognize the involvement of workers in planning and green management activities	Ahmad and Nisar [ ]
Encourage relations between employees to produce solutions to environmental issues. Examples: working groups and the elaboration of newsletters	Tang et al., Renwick et al., Daily and Huang [ , , ]
Provide incentives for workers to submit green initiatives/promote team activities (e.g., environmental project competition)	Bombiak and Marciniuk-Kluska, Likhitkar and Verma [ , ]

Category	Transversal Green Practices in the Organization	Author(s)
Digital	Preference for home office or hybrid/flexible work;	Mamatha and Bharmappa, Amutha [ , ]
	Preference for teleconferences, interviews, and virtual meetings (versus face-to-face meetings that require travel);
	Preference for digital manuals;
	Online training/e-learning.
Mobility	Company public transport, fleet of electric cars, bicycles;	Mamatha and Bharmappa, Amutha, Murari and Bhandari [ , , ]
	Subsidizing passes for use of public transport;
	Car-pooling policies (organize car-sharing framework);
	Preference for the use of stairs instead of elevators.
Products and waste	Total recycling of waste;	Mamatha and Bharmappa, Amutha, Murari and Bhandari [ , , ]
	Partnership with organizations that treat waste and give it new uses;
	Offer of ecological gifts (e.g., reusable shopping bags);
	Encourage workers to bring plates and mugs to avoid disposable ones;
	Preference for organic products (coffee or tea) and fair trade;
	Preference for recycled paper and recycled toners;
	Preference for providing filtered water instead of bottles;
	Avoid using polluting products (e.g., cleaning).
Infrastructures	Energy-efficient infrastructures (low-consumption lamps, timers on switches, photovoltaic panels);	Mamatha and Bharmappa, Amutha, Murari and Bhandari, Opatha and Arulrajah [ , , , ]
	Preference for office materials and furniture made from recycled materials;
	Provide parking for bicycles/electric cars;
	Green infrastructures using plants;
	Large spaces with natural light to reduce electricity consumption (connect the smallest number of lamps).
Performance	Elimination of workers’ identification cards;	Mamatha and Bharmappa, Amutha, Murari and Bhandari, Opatha and Arulrajah [ , , , ]
	Reducing the number of prints on paper and avoiding color printing (green printing);
	Preference for electronically filling out documents and digital files;
	Conducting regular energy audits;
	Consumption of natural water instead of refrigerated water (reduce electricity costs);
	Avoid leaks in drainage systems for efficient use of water;
	Shut down the computer when not used (instead of hibernating).
Production	Green production (care in the use of water and the drainage system; use of low-harm chemicals);	Mamatha and Bharmappa, Likhitkar and Verma, Amutha, Murari and Bhandari [ , , , ]
Production	Use of alternative energies (solar, wind);
Corporate events	Encourage plantations/vegetable gardens on company premises and workers’ homes.	Mamatha and Bharmappa, Amutha, Murari and Bhandari [ , , ]
	Develop environmental corporate activities involving all stakeholders (improves green identity and brand image);
	Planting trees on workers’ birthdays or annually (promotes green spaces and worker recognition).

	Macro (Society)	Meso (Organization)	Micro (Worker)	Author(s)
Benefits		Promotes a competitive advantage through economics and environmental sustainability		Renwick et al., Jabbour and de Sousa Jabbour, González-Benito and González-Benito [ , , ]
		Allows the organization to analyze its environmental impact and solutions for improvement		Farzana [ ]
		Promotes a healthy working environment (green spaces, less paper consumption)		Opatha and Arulrajah, Farzana [ , ]
	Preserve the environment and its sustainability			Mehta and Chugan, Farzana [ , ]
			Increases the motivation and confidence of workers by allowing them to conduct environmentally friendly practices	Likhitkar and Verma, Farzana [ , ]
			Improves the relationship between management/bosses and workers	Likhitkar and Verma [ ]
		Improves organizational reputation	Increases the retention rate of customers and workers	Likhitkar and Verma [ ] Muisyo et al. [ ]
			Increases employee loyalty and well-being	Likhitkar and Verma [ ]
		Allows the organization to improve its performance		Deshwal, Likhitkar and Verma [ , ]
		Reduces the company’s overall costs		Deshwal, Opatha and Arulrajah [ , ]
	The balance between financial performance and environmental protection			Daily and Huang, O’Donohue and Torugsa [ , ]
	Emergence of new, more sustainable business opportunities			Santos et al. [ ]
Constraints		The non-green environmental culture of the organization	Factors inherent to the worker (personality, values, lifestyle)	Labella-Fernández and Martínez-del-Río, Vahdati and Vahdati [ , ]
		Limited digital capacity of the organization (at the technological level—equipment)	Pressure on time management and efficiency of functions	Labella-Fernández and Martínez-del-Río, Vahdati and Vahdati [ , ]
		Fragile internal communication channels	Knowledge of the worker (qualifications, knowledge, digital literacy)	Labella-Fernández and Martínez-del-Río, Vahdati and Vahdati [ , ]
		High investment and low return (initial phase)	Different motivations for the environment among workers	Mehta and Mehta [ ] Kodua et al. [ ]
		Lack of environmental guidance from the top levels of the organization		Tanova and Bayighomog [ ]
	Lack of adaptation of some sectors of activity			Amrutha and Geetha [ ]
Challenges		Implement GHRM planning across the entire organization		Farzana [ ]
		Lack of green infrastructures and technologies		Farzana [ ]
	Need for continuous process development, marked by global trends and regulatory instruments			Agrawala et al. [ ]
		Difficulty in transforming a traditional HRM attitude to GHRM	Difficulty in measuring the effectiveness of GHRM practices on workers’ behavior	Mehta and Mehta [ ]
		Implementing a green culture is a time-consuming and complex process		Mehta and Mehta [ ]
			A lack of knowledge in environmental matters can generate limitations and a lack of cooperation between the organization’s specialists	Fayyazi et al. [ ]

	Practices Identified
Digital	Preference for hybrid work E-learning training
Mobility	Fleet renewal for electrics Promotion of car-sharing Encouraging the use of public transport and electric bicycles
Products and waste	System of waste separation and management Preference for the use of recycled articles and organic products Welcome kit with sustainable items (e.g., bottles, mugs) Use of filtered water systems Promotion of a fair trade and circular economy
Infrastructures	Eco-design and creation of outdoor green spaces More sustainable facilities with good energy efficiency Acquisition of recycled furniture Car parks with electric charging stations
Performance	Actions in terms of saving water and equipment energy Acquisition of more sustainable systems Elimination of access cards
Production	Use of renewable solutions to support energy costs (e.g., photovoltaic panels)
Corporate events	Cleaning beaches or green spaces Tree planting Actions to raise awareness of biodiversity and nature within the workers or the community Investment in green gamification

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Coelho, J.P.; Couto, A.I.; Ferreira-Oliveira, A.T. Green Human Resource Management: Practices, Benefits, and Constraints—Evidence from the Portuguese Context. Sustainability 2024 , 16 , 5478. https://doi.org/10.3390/su16135478

Coelho JP, Couto AI, Ferreira-Oliveira AT. Green Human Resource Management: Practices, Benefits, and Constraints—Evidence from the Portuguese Context. Sustainability . 2024; 16(13):5478. https://doi.org/10.3390/su16135478

Coelho, Joana Patrícia, Ana Isabel Couto, and Ana Teresa Ferreira-Oliveira. 2024. "Green Human Resource Management: Practices, Benefits, and Constraints—Evidence from the Portuguese Context" Sustainability 16, no. 13: 5478. https://doi.org/10.3390/su16135478

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empirical evidence

3.7. Becoming a linguist: Empirical and theoretical arguments

Empirical arguments

Making observations

Making a theoretical claim

Backing up your claim

Theoretical arguments

Laying out your premises

Drawing a conclusion

Consider your assumptions

Presenting your argument

Check yourself!

Empirical evidence: A definition

The scientific method

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Oromotor Nonverbal Performance and Speech Motor Control: Theory and Review of Empirical Evidence

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Oromotor Nonverbal Performance and Speech Motor Control: Theory and Review of Empirical Evidence

1. Introduction

1.2. Purposes of the Present Paper

2. Definitions

2.1.1. Speech Motor Control

2.1.2. Motor Speech Disorder

2.1.3. Dysarthria

2.1.4. Apraxia of Speech

2.1.5. Oromotor, Nonverbal Tasks (Nonspeech Oromotor (NSOM) Tasks)

2.1.6. Task Specificity

2.1.7. Quasi-Speech Tasks

2.1.8. Subsystems

2.1.9. Mechanism

3. Preliminary Considerations

3.2. Can Performance on Oromotor Tasks Be Reconciled with Speech Production Deficits in Diseases/Dysarthrias?

4. Two Models of Speech Motor Control

4.1.1. Structure of IM

4.1.2. Predictions from the IM

4.1.3. Structure of the TDM

4.1.4. Predictions of TDM

4.2. Structure and Predictions from the IM and TDM: Summary

5. Task Specificity

5.2. Dystonia as a Task Specific Disorder

5.3. Motor Learning and Task Specificity

5.4. We Are Talking about Task Specificity

5.5. Accounting for Task Specificity without a Special Module

6. Empirical Findings

6.2. Published Reviews

6.3. Studies of Oromotor, Nonverbal Measures and Speech Performance in Healthy Individuals

6.3.2. Mixed Findings

6.3.3. Negative Findings

6.4. Studies of Oromotor, Nonverbal Measures and Speech Performance in Individuals with Motor Speech Disorders and Other Selected Speech Disorders

6.4.1. Positive Findings

6.4.2. Mixed Findings

6.4.3. Negative Findings

7. A Note on DDK

8. Overall Summary

Acknowledgments

Funding Statement

Conflicts of Interest

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Second Language Speech Learning

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Second Language Speech Learning pp i-ii

Second Language Speech Learning - Title page pp iii-iii

Copyright page pp iv-iv

Chapter 2 - The Revised Speech Learning Model (SLM-r) Applied pp 84-118