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 [BibTeX] [Marc21]
User-Customized Password Speaker Verification based on HMM/ANN and GMM Models
Type of publication: Idiap-RR
Citation: BenZeghiba-02a
Number: Idiap-RR-10-2002
Year: 2002
Institution: IDIAP
Note: published in ICSLP 2002
Abstract: In this paper, we present a new approach towards user-custom\-ized password speaker verification combining the advantages of hybrid HMM/ANN systems, using Artificial Neural Networks (ANN) to estimate emission probabilities of Hidden Markov Models, and Gaussian Mixture Models. In the approach presented here, we indeed exploit the properties of hybrid HMM/ANN systems, usually resulting in high phonetic recognition rates, to automatically infer the baseline phonetic transcription (HMM topology) associated with the user customized password from a few enrollment utterances and using a large, speaker independent, ANN. The emission probabilities of the resulting HMMs are then modeled in terms of speaker specific/adapted multi-Gaussian HMMs or speaker specific/adapted ANN. In the proposed approach, the hybrid HMM/ANN system is used as a model for utterance (password) verification, while still using a speaker independent GMM for speaker verification. Results (EER) are compared to a state-of-the-art text-dependent approach, using multi-Gaussian HMMs only.
Userfields: ipdmembership={speech},
Projects Idiap
Authors BenZeghiba, Mohamed Faouzi
Bourlard, Hervé
Crossref by BenZeghiba_icslp-02
Added by: [UNK]
Total mark: 0
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