Speech feature extracted from adaptive wavelet forspeech recognition
Authors:
- Sung-Il YangSYSung-Il Yang
- 12 November 1998
- journal article
- Published by Institution of Engineering and Technology (IET) in Electronics Letters
- Vol. 34 (23) , 2211-2213
Abstract
A new speech feature extracted from adaptive wavelet for speech recognition is described. 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.Keywords
This publication has 1 reference indexed in Scilit:
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