Mandarin tone recognition based on wavelet transform and hidden Markov modeling |
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Authors: | Jun Cheng Kechu Yi Bingbing Li |
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Affiliation: | (1) National Key Laboratory on ISN, Xidian University, 710071 Xi’an |
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Abstract: | This paper presents a method of tone recognition for Mandarin speech by using combination of wavelet transform and hidden Markov modeling techniques. A pitch detector based on singularity detection and multi-resolution analysis of wavelet transform is employed for estimation of pitch periods, and hidden Markov modeling with partition Gaussian mixtures probability density function is used for the tone recognition. The algorithm can provide recognition accuracy of 97.22% and 94.47% for speaker-dependent and speaker-independent tone recognition, respectively. |
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Keywords: | Pitch detection Tone recognition Wavelet transform Hidden Markov model |
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