Speech feature extracted from adaptive wavelet forspeech recognition
Sungwook Chang, Y. Kwon, Sung-Il Yang · Electronics Letters · 1998
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.