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Automatic Speaker Recognition

Text Independent Automatic Speaker Recognition System Using Mel Frequency Cepstrum Coefficient and Gaussian Mixture Models

Text Independent Automatic Speaker Recognition System Using Mel Frequency Cepstrum Coefficient and Gaussian Mixture Models

... independent automatic speaker recognition (ASR) system, based on Mel-Frequency Cepstrum Coefficients (MFCC) and Gaussian Mixture Models (GMM), in or- der to develop a security control access ...each ...

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Automatic Speaker Recognition System For Forensic Applications

Automatic Speaker Recognition System For Forensic Applications

... This chapter covers the explanation about the main concept of automatic speaker recognition system for forensic application. Other than that, the main reason why the project is needed is also cover ...

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Bayesian distance metric learning and its application in automatic speaker recognition systems

Bayesian distance metric learning and its application in automatic speaker recognition systems

... the-art Automatic Speaker Recognition System (ASR) based on Bayesian Distance Learning Metric as a feature ...same speaker and different ...a speaker tag, I select the data pair of the ...

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Studies on automatic speaker recognition

Studies on automatic speaker recognition

... Ther efore if the mism atch betw een the real distr ibuti on of a spea ker's data and the estim ated distr ibuti on with GM mod el form causes reco gniti on error s, thos e error s occu [r] ...

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Comparative Analysis of Automatic Speaker Recognition using Kekre’s Fast Codebook Generation Algorithm in Time and Transform Domain

Comparative Analysis of Automatic Speaker Recognition using Kekre’s Fast Codebook Generation Algorithm in Time and Transform Domain

... For speaker identification, the codebook of the test sample is similarly generated and compared with the codebooks of the reference samples stored in the ...

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Automatic Speaker Recognition System in Adverse Conditions — Implication of Noise and Reverberation on System Performance

Automatic Speaker Recognition System in Adverse Conditions — Implication of Noise and Reverberation on System Performance

... The image-source model (ISM) [18] is a technique used to generate synthetic room impulse responses (RIRs). Once the RIR is available, reverberated speech samples can be simulated by converlution according to (2). The ISM ...

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Speaker Recognition System and Algorithms

Speaker Recognition System and Algorithms

... for Automatic Speaker Recognition Systems has been ...done. Speaker recognition is that the method of automatically recognizing who is speaking on the premise of individual info ...

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AUTOMATED SPEAKER RECOGNITION METHODS: A CRITICAL REVIEW

AUTOMATED SPEAKER RECOGNITION METHODS: A CRITICAL REVIEW

... of speaker recognition technology is ...integrate automatic speaker recognition to appendix auricular and semi-automatic analysis ...speech recognition and semantic ...

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A Method to Integrate GMM, SVM and DTW for Speaker Recognition

A Method to Integrate GMM, SVM and DTW for Speaker Recognition

... for automatic speaker ...for speaker recognition ...speech recognition, and it will be employed to be a verifier for verification of valid ...for speaker recognition in ...

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Assessment of Severe Apnoea through Voice Analysis, Automatic Speech, and Speaker Recognition Techniques

Assessment of Severe Apnoea through Voice Analysis, Automatic Speech, and Speaker Recognition Techniques

... GMM-based automatic speaker recognition techniques [15] to try to observe possible peculiarities in apnoea patients’ ...allow automatic (and rapid) diagnosis of the ...on automatic ...

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Speaker Recognition Using Machine Learning Techniques

Speaker Recognition Using Machine Learning Techniques

... Building up on the research by Schmidt et al., Campos et al. in 2016 studied vector quantization and unsupervised learning for speaker recognition [9]. Vector quantization is defined as generating a set of ...

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A study into automatic speaker verification with aspects of deep learning

A study into automatic speaker verification with aspects of deep learning

... Ghahremani et al [93] describe the motivation for calculating the mean and standard deviation over a moving input window to the network, as expecting to capture long term variability effects in the speaker and ...

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Ensemble Models for Spoofing Detection in Automatic Speaker Verification

Ensemble Models for Spoofing Detection in Automatic Speaker Verification

... Detecting spoofing attempts of automatic speaker verification (ASV) systems is challenging, especially when using only one modelling approach. For robustness, we use both deep neural networks and ...

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Speaker Recognition using Gaussian Mixture Model

Speaker Recognition using Gaussian Mixture Model

... In this paper, the air conducted speech signals are recorded from different speakers using a standard microphone and also with the another mode of speech recording using a throat microphone.The recorded speech signals ...

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Speaker Independent Phone Recognition Using BREF

Speaker Independent Phone Recognition Using BREF

... Speaker Independent Phone Recognition Using BREF Speaker Independent Phone Recognition Using BREF Jean Luc Gauvain a n d Lori F L a m e l L I M S I C N R S , B P 133 9 1 4 0 3 O r s a y c e d e x , F[.] ...

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Information fusion for subband HMM speaker recognition

Information fusion for subband HMM speaker recognition

... Our earlier work has demonstrated the performance gains that can be obtained in speaker recognition by applying subband processing, together with hidden Markov models and multiple classi[r] ...

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On the Use of Complementary Spectral Features for Speaker Recognition

On the Use of Complementary Spectral Features for Speaker Recognition

... The expectation maximization (EM) algorithm [23] was used to estimate the parameters of the GMM. Although the EM algorithm is an unsupervised clustering algorithm, it cannot estimate the model order and it also requires ...

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Automatic recognition by gait

Automatic recognition by gait

... The approaches derive the human silhouette by sep- arating the moving object from the background. Then, the subject can be recognized by measurements that reflect shape and/or movement. Some techniques impose a model of ...

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Automatic Gait Recognition

Automatic Gait Recognition

... there is a view that gait can be used to recognize individuals. While the examination of gait as a biometric is promising, there are limits to the utility of gait information. Most obviously, gait can be obscured by ...

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Multi-speaker frequency warping vocal tract length normalization for speaker independent speech recognition

Multi-speaker frequency warping vocal tract length normalization for speaker independent speech recognition

... and recognition process involves longer speech processing time as well as larger storage resources ...phoneme recognition, which focuses on recognizing phonemes from every speech input, into a very delicate ...

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