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Phoneme Weighting And Energy-Based Weighting For Speaker Recognition, Eric Fang

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This dissertation focuses on determining specific vowel phonemes which work best for speaker identification and speaker verification, and also developing new algorithms to improve speaker identification accuracy. Results from the first part of our research indicate that the vowels /i/, /E/ and /u/ were the ones having the highest recognition scores for both the Gaussian mixture model (GMM) and vector quantization (VQ) methods (at most one classification error). For VQ, /i/, /I/, /e/, /E/ and /@/ had no classification errors. Persons speaking /E/, /o/ and /u/ have been verified well by both GMM and VQ methods in our experiments. For …