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VoxCeleb1 Benchmark (Speaker Identification)
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A review on speaker recognition: Technology and challenges
This paper provides a comprehensive review of the literature on speaker recognition. It discusses the advances made in the last decade, including the challenges in this area of research. This paper also highlights the system and structure of speaker recognition as well as its feature extraction and classifiers.
Speaker recognition based on deep learning: An overview
Speaker recognition is a task of identifying persons from their voices. Recently, deep learning has dramatically revolutionized speaker recognition. However, there is lack of comprehensive reviews on the exciting progress. In this paper, we review several major subtasks of speaker recognition, including speaker verification, identification ...
Speaker identification through artificial intelligence techniques: A
The contributions of this paper are as follows: ... The details of different benchmark speech databases utilized by various research studies for speaker identification is presented below. VoxCeleb (Nagrani et al., 2017) is a large-scale SI database derived from YouTube videos. VoxCeleb is an English language-based speech database that includes ...
A Deep Neural Network Model for Speaker Identification
Speaker identification is a classification task which aims to identify a subject from a given time-series sequential data. Since the speech signal is a continuous one-dimensional time series, most of the current research methods are based on convolutional neural network (CNN) or recurrent neural network (RNN). Indeed, these methods perform well in many tasks, but there is no attempt to combine ...
Deep Speaker Recognition: Process, Progress, and Challenges
Abstract: Speaker recognition is related to human biometrics dealing with the identification of speakers from their speech. Speaker recognition is an active research area and being widely investigated using artificially intelligent mechanisms. Though speaker recognition systems were previously constructed using handcrafted statistical means of machine learning, currently it is being shifted to ...
Analysis of Methods and Techniques Used for Speaker Identification
In this paper, research-related publications of the past 25 years (from 1996 to 2020) were studied and analysed. Our main focus was on speaker identification, speaker recognition, and speaker ...
Deep Learning-Based End-to-End Speaker Identification Using ...
Research on speaker identification started in the early 1960s [].There has been a lot of work done and substantial progress made. Hidden Markov models [] and Gaussian mixture models (GMMs) [] are the most prominent stochastic techniques for speaker identification.The common template-based modeling approaches considered by researchers include vector quantization (VQ) and dynamic time warping ...
A review on Deep Learning approaches in Speaker Identification
This paper is motivated to reduce this knowledge gap and to promote the research of implementing deep learning techniques for speaker identification. In this paper, we present a review of the DL methodologies used for speaker identification and surveys important DL algorithms that can potentially be explored for future works.
PDF arXiv:2012.00931v2 [eess.AS] 4 Apr 2021
speaker recognition to a new level, even in wild environments [15, 16]. In this survey article, we give a comprehensive overview to the deep learning based speaker recognition methods in terms of the vital subtasks and research topics, including speaker ver-ification, identification, diarization, and robust speaker recogni-tion.
Analysis and Investigation of Speaker Identification Problems ...
The rapid momentum of deep neural networks (DNNs) in recent years has yielded state-of-the-art performance in various machine-learning tasks using speaker identification systems. Speaker identification is based on the speech signals and the features that can be extracted from them. In this article, we proposed a speaker identification system using the developed DNNs models. The system is based ...
Conception of Speaker Recognition Methods: A Review
Abstract: In the last decade, the speaker recognition systems know a wide interest from many researchers of speech and speaker recognition technologies that led this technology to become a practical identity authentication means. This paper reviews the speaker recognition systems evolution from the first implementation to current trends. In this paper, we present a brief overview of the ...
Learning Deep Embedding with Acoustic and Phoneme Features for Speaker
The field of speaker recognition can be categorized into two main tasks: speaker identification (SI) and speaker verification (SV). SI is focused on identifying the speaker's identity, while SV seeks to authenticate whether the speaker is the target individual. ... In this paper, we propose a deep speaker embedding learning approach, which ...
Recurrence plot embeddings as short segment nonlinear features for
The speaker identification experiments on the CMT corpus are to demonstrate the speaker-discriminative ability of the joint RP embeddings of the multimodal data obtained from complementary modes ...
(PDF) A Survey of Speaker Recognition: Fundamental Theories
This paper briefly describes all the main aspects of ASR, such as speaker identification, verification, diarization etc. Further, the performance of current speaker recognition systems are ...
Speaker Identification using Speech Recognition
This paper will mainly focus on speaker identification, and in some cases, speaker verification as well. This research can later on serve as a basis for multi-speaker identification as well, where we identify multiple speakers in an audio. Abdul Basit Mughal Department of Computer Science School of Engineering and Applied Sciences (SEAS) Bahria ...
Speaker Identification
Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets. ... we propose a portable model called Additive Margin MobileNet1D (AM-MobileNet1D) to Speaker Identification on mobile devices. 3. Paper Code ... Papers With Code is a free resource with all data licensed under CC-BY-SA.
Speaker Recognition Based on Deep Learning: An Overview
Speaker recognition is a task of identifying persons from their voices. Recently, deep learning has dramatically revolutionized speaker recognition. However, there is lack of comprehensive reviews on the exciting progress. In this paper, we review several major subtasks of speaker recognition, including speaker verification, identification, diarization, and robust speaker recognition, with a ...
A Survey of Speaker Recognition: Fundamental Theories, Recognition
Specifically, this literature survey gives a concise introduction to ASR and provides an overview of the general architectures dealing with speaker recognition technologies, and upholds the past, present, and future research trends in this area. This paper briefly describes all the main aspects of ASR, such as speaker identification ...
An investigation towards speaker identification using a single-sound
Using Speaker Recognition (SR) technologies to identify the speaker from a given utterance by comparing voice biometrics of the given speaker is known as automatic Speaker Identification (SI) [].Particularly, it is the process to compare one user voice profile against many profiles and find the best or exact match [].The most important aspect of using SI systems is for automating processes ...
Speaker identification features extraction methods: A systematic review
Research identification: initial search using speaker recognition as the keyword without any filters resulted in 1710 papers from IEEE Xplore, 34,045 from ScienceDirect, 6678 from ACM digital library, and 36,676 from Springer Verlag. Resources with combined results from multiple sources like Google Scholar and DBLP resulted in 1160,000 and 764 ...
A speaker identification-verification approach for noise ...
The degraded quality of the speech input signal has a negative impact on speaker recognition techniques. We address the issues of speaker recognition from noise-corrupted audio signals in the presence of four noise variants, including factory noise, car noise, street traffic noise, and voice babble noise, as well as noise-suppressed enhanced speech. The goal of this research is to create a ...
A speaker identification-verification approach for noise-corrupted and
Semantic Scholar extracted view of "A speaker identification-verification approach for noise-corrupted and improved speech using fusion features and a convolutional neural network" by Rohun Nisa et al. ... This research aims to use Hidden Markov Model (HMM) based automatic speech recognition system to analyze the cough signal and determine ...
An Overview of Speaker Identification: Accuracy and Robustness Issues
This paper presents the main paradigms for speaker identification, and recent work on missing data methods to increase robustness. The feature extraction, speaker modeling and system classification are discussed. Evaluations of speaker identification performance subject to environmental noise are presented. While performance is impressive in clean speech conditions, there is rapid degradation ...
Speaker Identification using MFCC-Domain Support Vector Machine
Abstract: Speech recognition and speaker identification are important for authentication and verification in security purpose, but they are difficult to achieve. Speaker identification methods can be divided into text-independent and text-dependent. This paper presents a technique of text-dependent speaker identification using MFCC-domain ...
(PDF) Forensic Speaker Identification: A tutorial
This paper presents an overview of the methodologies used in the forensic field for the identification of speakers. First, an introduction shows the interest of the forensic community in speaker ...
Automatic speaker recognition technology outperforms human listeners in
APA. Chicago. Aston University. "Automatic speaker recognition technology outperforms human listeners in the courtroom." ScienceDaily. ScienceDaily, 7 November 2022. <www.sciencedaily.com ...
[2205.14649] Speaker Identification using Speech Recognition
Speaker Identification using Speech Recognition. Syeda Rabia Arshad, Syed Mujtaba Haider, Abdul Basit Mughal. The audio data is increasing day by day throughout the globe with the increase of telephonic conversations, video conferences and voice messages. This research provides a mechanism for identifying a speaker in an audio file, based on ...
Genetic and Genomic Pathways to Improved Wheat
Wheat (Triticum aestivum L.) is a fundamental crop essential for both human and animal consumption. Addressing the challenge of enhancing wheat yield involves sophisticated applications of molecular genetics and genomic techniques. This review synthesizes current research identifying and characterizing pivotal genes that impact traits such as grain size, number, and weight, critical factors ...
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This paper provides a comprehensive review of the literature on speaker recognition. It discusses the advances made in the last decade, including the challenges in this area of research. This paper also highlights the system and structure of speaker recognition as well as its feature extraction and classifiers.
Speaker recognition is a task of identifying persons from their voices. Recently, deep learning has dramatically revolutionized speaker recognition. However, there is lack of comprehensive reviews on the exciting progress. In this paper, we review several major subtasks of speaker recognition, including speaker verification, identification ...
The contributions of this paper are as follows: ... The details of different benchmark speech databases utilized by various research studies for speaker identification is presented below. VoxCeleb (Nagrani et al., 2017) is a large-scale SI database derived from YouTube videos. VoxCeleb is an English language-based speech database that includes ...
Speaker identification is a classification task which aims to identify a subject from a given time-series sequential data. Since the speech signal is a continuous one-dimensional time series, most of the current research methods are based on convolutional neural network (CNN) or recurrent neural network (RNN). Indeed, these methods perform well in many tasks, but there is no attempt to combine ...
Abstract: Speaker recognition is related to human biometrics dealing with the identification of speakers from their speech. Speaker recognition is an active research area and being widely investigated using artificially intelligent mechanisms. Though speaker recognition systems were previously constructed using handcrafted statistical means of machine learning, currently it is being shifted to ...
In this paper, research-related publications of the past 25 years (from 1996 to 2020) were studied and analysed. Our main focus was on speaker identification, speaker recognition, and speaker ...
Research on speaker identification started in the early 1960s [].There has been a lot of work done and substantial progress made. Hidden Markov models [] and Gaussian mixture models (GMMs) [] are the most prominent stochastic techniques for speaker identification.The common template-based modeling approaches considered by researchers include vector quantization (VQ) and dynamic time warping ...
This paper is motivated to reduce this knowledge gap and to promote the research of implementing deep learning techniques for speaker identification. In this paper, we present a review of the DL methodologies used for speaker identification and surveys important DL algorithms that can potentially be explored for future works.
speaker recognition to a new level, even in wild environments [15, 16]. In this survey article, we give a comprehensive overview to the deep learning based speaker recognition methods in terms of the vital subtasks and research topics, including speaker ver-ification, identification, diarization, and robust speaker recogni-tion.
The rapid momentum of deep neural networks (DNNs) in recent years has yielded state-of-the-art performance in various machine-learning tasks using speaker identification systems. Speaker identification is based on the speech signals and the features that can be extracted from them. In this article, we proposed a speaker identification system using the developed DNNs models. The system is based ...
Abstract: In the last decade, the speaker recognition systems know a wide interest from many researchers of speech and speaker recognition technologies that led this technology to become a practical identity authentication means. This paper reviews the speaker recognition systems evolution from the first implementation to current trends. In this paper, we present a brief overview of the ...
The field of speaker recognition can be categorized into two main tasks: speaker identification (SI) and speaker verification (SV). SI is focused on identifying the speaker's identity, while SV seeks to authenticate whether the speaker is the target individual. ... In this paper, we propose a deep speaker embedding learning approach, which ...
The speaker identification experiments on the CMT corpus are to demonstrate the speaker-discriminative ability of the joint RP embeddings of the multimodal data obtained from complementary modes ...
This paper briefly describes all the main aspects of ASR, such as speaker identification, verification, diarization etc. Further, the performance of current speaker recognition systems are ...
This paper will mainly focus on speaker identification, and in some cases, speaker verification as well. This research can later on serve as a basis for multi-speaker identification as well, where we identify multiple speakers in an audio. Abdul Basit Mughal Department of Computer Science School of Engineering and Applied Sciences (SEAS) Bahria ...
Stay informed on the latest trending ML papers with code, research developments, libraries, methods, and datasets. ... we propose a portable model called Additive Margin MobileNet1D (AM-MobileNet1D) to Speaker Identification on mobile devices. 3. Paper Code ... Papers With Code is a free resource with all data licensed under CC-BY-SA.
Speaker recognition is a task of identifying persons from their voices. Recently, deep learning has dramatically revolutionized speaker recognition. However, there is lack of comprehensive reviews on the exciting progress. In this paper, we review several major subtasks of speaker recognition, including speaker verification, identification, diarization, and robust speaker recognition, with a ...
Specifically, this literature survey gives a concise introduction to ASR and provides an overview of the general architectures dealing with speaker recognition technologies, and upholds the past, present, and future research trends in this area. This paper briefly describes all the main aspects of ASR, such as speaker identification ...
Using Speaker Recognition (SR) technologies to identify the speaker from a given utterance by comparing voice biometrics of the given speaker is known as automatic Speaker Identification (SI) [].Particularly, it is the process to compare one user voice profile against many profiles and find the best or exact match [].The most important aspect of using SI systems is for automating processes ...
Research identification: initial search using speaker recognition as the keyword without any filters resulted in 1710 papers from IEEE Xplore, 34,045 from ScienceDirect, 6678 from ACM digital library, and 36,676 from Springer Verlag. Resources with combined results from multiple sources like Google Scholar and DBLP resulted in 1160,000 and 764 ...
The degraded quality of the speech input signal has a negative impact on speaker recognition techniques. We address the issues of speaker recognition from noise-corrupted audio signals in the presence of four noise variants, including factory noise, car noise, street traffic noise, and voice babble noise, as well as noise-suppressed enhanced speech. The goal of this research is to create a ...
Semantic Scholar extracted view of "A speaker identification-verification approach for noise-corrupted and improved speech using fusion features and a convolutional neural network" by Rohun Nisa et al. ... This research aims to use Hidden Markov Model (HMM) based automatic speech recognition system to analyze the cough signal and determine ...
This paper presents the main paradigms for speaker identification, and recent work on missing data methods to increase robustness. The feature extraction, speaker modeling and system classification are discussed. Evaluations of speaker identification performance subject to environmental noise are presented. While performance is impressive in clean speech conditions, there is rapid degradation ...
Abstract: Speech recognition and speaker identification are important for authentication and verification in security purpose, but they are difficult to achieve. Speaker identification methods can be divided into text-independent and text-dependent. This paper presents a technique of text-dependent speaker identification using MFCC-domain ...
This paper presents an overview of the methodologies used in the forensic field for the identification of speakers. First, an introduction shows the interest of the forensic community in speaker ...
APA. Chicago. Aston University. "Automatic speaker recognition technology outperforms human listeners in the courtroom." ScienceDaily. ScienceDaily, 7 November 2022. <www.sciencedaily.com ...
Speaker Identification using Speech Recognition. Syeda Rabia Arshad, Syed Mujtaba Haider, Abdul Basit Mughal. The audio data is increasing day by day throughout the globe with the increase of telephonic conversations, video conferences and voice messages. This research provides a mechanism for identifying a speaker in an audio file, based on ...
Wheat (Triticum aestivum L.) is a fundamental crop essential for both human and animal consumption. Addressing the challenge of enhancing wheat yield involves sophisticated applications of molecular genetics and genomic techniques. This review synthesizes current research identifying and characterizing pivotal genes that impact traits such as grain size, number, and weight, critical factors ...