Normalizing the vocal tract length for speaker independent speech recognition
Qiguang Lin, ChiWei Che
Abstract
Qiguang Lin, ChiWei Che
Abstract
We overall vocal-tract length differs between individuals. The difference is more apparent between males and females. In this work, a new method is presented which normalizes the overall vocal-tract length in the cepstrum domain. By properly selecting the upper frequency of a FFT spectrum, the derived cepstrum coefficients exhibit a pattern which is less susceptible to the length variations. The proposed method is evaluated in isolated-word speech recognition experiments where a recognizer was exclusively trained on male speech and tested on female speech, and vice versa. The method elevated the word recognition accuracy from 57.0 to 78.8% and from 70.5 to 86.1%, respectively.>
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We overall vocal-tract length differs between individuals. The difference is more apparent between males and females. In this work, a new method is presented which normalizes the overall vocal-tract length in the cepstrum domain. By properly selecting the upper frequency of a FFT spectrum, the derived cepstrum coefficients exhibit a pattern which is less susceptible to the length variations. The proposed method is evaluated in isolated-word speech recognition experiments where a recognizer was exclusively trained on male speech and tested on female speech, and vice versa. The method elevated the word recognition accuracy from 57.0 to 78.8% and from 70.5 to 86.1%, respectively.>
Key concepts: Vocal tract, Speech recognition, Cepstrum, Mel-frequency cepstrum, Computer science, Word (group theory), Fast Fourier transform, Pattern recognition (psychology)