Speaker verification using phoneme-adapted Gaussian Mixture Models

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.