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Paper data
Speaker Verification using Phoneme-Adapted Gaussian Mixture Models

Gutman Dan, Tel Aviv University
Bistritz Yuval, Tel Aviv University

Page numbers in the proceedings:
Volume III pp 85-88

Multimedia Data Protection / Speech Analysis and Recognition

Paper abstract
Despite intuitive expectation and experimental evidence that phonemes contain useful speaker discriminating information, phoneme-based speaker recognition systems reported so far were not found to perform better than phoneme-independent speaker recognition systems based on Gaussian Mixture Model (GMM). The paper proposes a new phoneme-based speaker verification technique that uses models obtained by adaptation of well-trained speaker GMMs. The new proposed system was found to consistently outperform comparable sized phoneme-independent GMM based speaker verification systems in experiments held with clean and telephone speech databases.

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