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A Tutorial on Text-Independent Speaker Verification
- EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING 2004:4, 430–451
, 2004
"... This paper presents an overview of a state-of-the-art text-independent speaker verification system. First, an introduction proposes a modular scheme of the training and test phases of a speaker verification system. Then, the most commonly speech parameterization used in speaker verification, namely, ..."
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Cited by 138 (13 self)
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This paper presents an overview of a state-of-the-art text-independent speaker verification system. First, an introduction proposes a modular scheme of the training and test phases of a speaker verification system. Then, the most commonly speech parameterization used in speaker verification, namely, cepstral analysis, is detailed. Gaussian mixture modeling, which is the speaker modeling technique used in most systems, is then explained. A few speaker modeling alternatives, namely, neural networks and support vector machines, are mentioned. Normalization of scores is then explained, as this is a very important step to deal with real-world data. The evaluation of a speaker verification system is then detailed, and the detection error trade-off (DET) curve is explained. Several extensions of speaker verification are then enumerated, including speaker tracking and segmentation by speakers. Then, some applications of speaker verification are proposed, including on-site applications, remote applications, applications relative to structuring audio information, and games. Issues concerning the forensic area are then recalled, as we believe it is very important to inform people about the actual performance and limitations of speaker verification systems. This paper concludes by giving a
Evolutive Hmm For Multi-Speaker Tracking System
, 2000
"... Seeking within a speech sequence the speaker utterances is one of the main tasks of indexing. ..."
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Cited by 13 (4 self)
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Seeking within a speech sequence the speaker utterances is one of the main tasks of indexing.
Bayesian Approach based-Decision in Speaker Verification
- In Proceedings of 2001: A Speaker Odyssey
, 2001
"... Considering Bayesian decision framework applied in the context of speaker verification, this paper presents a new way of handling troublesome anti-speaker model by proposing a redefinition of hypotheses involved in the classical statistical hypothesis test. This new definition of hypotheses is then ..."
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Cited by 7 (2 self)
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Considering Bayesian decision framework applied in the context of speaker verification, this paper presents a new way of handling troublesome anti-speaker model by proposing a redefinition of hypotheses involved in the classical statistical hypothesis test. This new definition of hypotheses is then implemented through a speaker independent normalization technique, named MAP approach. Besides supporting these new hypotheses, MAP approach takes the advantages of projecting likelihood scores into a probabilistic domain and therefore of providing the decision threshold with bounded and meaningful values.
ISCA Archive Bayesian Approach based-Decision in Speaker Verification
"... Considering Bayesian decision framework applied in the context of speaker verification, this paper presents a new way of handling troublesome anti-speaker model by proposing a redefinition of hypotheses involved in the classical statistical hypothesis test. This new definition of hypotheses is then ..."
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Considering Bayesian decision framework applied in the context of speaker verification, this paper presents a new way of handling troublesome anti-speaker model by proposing a redefinition of hypotheses involved in the classical statistical hypothesis test. This new definition of hypotheses is then implemented through a speaker independent normalization technique, named MAP approach. Besides supporting these new hypotheses, MAP approach takes the advantages of projecting likelihood scores into a probabilistic domain and therefore of providing the decision threshold with bounded and meaningful values. In this paper, different variants of MAP approach are presented which mainly aims at reducing likelihood variability, well-known in speaker verification to degrade system performance. MAP approach is firstly combined with classical normalization techniques (likelihood ratio normalization (world model) and/or Hnorm normalization technique). The second kind of variants consists in redesigning MAP approach to become speaker dependent. Experiments conducted on a subset of Switchboard database involving these different variants have showed that MAP approach is able to perform as well as classical normalization techniques while yielding probabilistic scores suitable for the decision threshold setting or the fusion of recognizer scores in the context of a multi-recognizer architecture. 1.
Research Article Reliability-Based Decision Fusion in Multimodal Biometric Verification Systems
"... We present a methodology of reliability estimation in the multimodal biometric verification scenario. Reliability estimation has showntobeanefficient and accurate way of predicting and correcting erroneous classification decisions in both unimodal (speech, face, online signature) and multimodal (spe ..."
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We present a methodology of reliability estimation in the multimodal biometric verification scenario. Reliability estimation has showntobeanefficient and accurate way of predicting and correcting erroneous classification decisions in both unimodal (speech, face, online signature) and multimodal (speech and face) systems. While the initial research results indicate the high potential of the proposed methodology, the performance of the reliability estimation in a multimodal setting has not been sufficiently studied or evaluated. In this paper, we demonstrate the advantages of using the unimodal reliability information in order to perform an efficient biometric fusion of two modalities. We further show the presented method to be superior to state-of-the-art multimodal decision-level fusion schemes. The experimental evaluation presented in this paper is based on the popular benchmarking bimodal BANCA database. Copyright © 2007 Krzysztof Kryszczuk et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1.
The ELISA Systems for the NIST'99 Evaluation in Speaker Detection and Tracking
, 2000
"... This article presents the text-independent speaker detection and track- ing systems developed by the members of the ELISA Consortium for the NIST'99 speaker recognition evaluation campaign. ELISA is a consortium grouping researchers of several laboratories sharing software modules, resources ..."
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This article presents the text-independent speaker detection and track- ing systems developed by the members of the ELISA Consortium for the NIST'99 speaker recognition evaluation campaign. ELISA is a consortium grouping researchers of several laboratories sharing software modules, resources and experimental protocols. Each system is briefly described, and comparative results on the NIST'99 evaluation tasks are discussed. 2000 Academic Press Key Words: text-independent, speaker verification, speaker detection, speaker tracking, NIST evaluation campaign 1.
A REVIEW OF VARIOUS SCORE NORMALIZATION TECHNIQUES FOR SPEAKER IDENTIFICATION SYSTEM
"... This paper presents an overview of a state-of-the-art text-independent speaker verification system using score normalization. First, an introduction proposes a modular scheme of the training and test phases of a speaker verification system. Then, the most commonly speech parameterization used in spe ..."
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This paper presents an overview of a state-of-the-art text-independent speaker verification system using score normalization. First, an introduction proposes a modular scheme of the training and test phases of a speaker verification system. Then, the most commonly speech parameterization used in speaker verification, namely, cepstral analysis, is detailed. Normalization of scores is then explained, as this is a very important step to deal with real-world data. When acoustic and prosodic based systems are established, it is advantageous to normalize the dynamic ranges of the score dimensions, that is, likelihood scores from different quality of acoustic- and prosodic based models. Score normalization methods, linear scaling to unit range and linear scaling to unit variance, are applied to transform the output scores using the background instances so as to obtain meaningful comparison between speaker models. In this fusion system based on linear score weighting approach, the performance of speaker identification is further improved when incorporating prosodic level of information. The evaluation of a speaker verification system is then detailed, and the detection error trade-off (DET) curve is explained.. Then, some applications of speaker verification are proposed, including won-site applications, remote applications, applications relative to structuring audio information, and games.
