Speech feature extracted from adaptive wavelet for speechrecognition |
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Authors: | Sungwook Chang Kwon Y. Sung-Il Yang |
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Affiliation: | Dept. of Control & Instrum. Eng., Hanyang Univ., Seoul; |
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Abstract: | The speech signal is decomposed through adapted local trigonometric transforms. The decomposed signal is classified by M uniform sub-bands for each subinterval. The energy of each sub-band is used as a speech feature. This feature is applied to vector quantisation and the hidden Markov model. The new speech feature shows a slightly better recognition rate than the cepstrum for speaker independent speech recognition. The new speech feature also shows a lower standard deviation between speakers than does the cepstrum |
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