DocumentCode
1463786
Title
Speech feature extracted from adaptive wavelet for speech recognition
Author
Chang, Sungwook ; Kwon, Y. ; Yang, Sung-il
Author_Institution
Dept. of Control & Instrum. Eng., Hanyang Univ., Seoul, South Korea
Volume
34
Issue
23
fYear
1998
fDate
11/12/1998 12:00:00 AM
Firstpage
2211
Lastpage
2213
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
Keywords
adaptive signal processing; feature extraction; hidden Markov models; speaker recognition; speech processing; vector quantisation; wavelet transforms; adapted local trigonometric transforms; adaptive wavelet; decomposed signal; feature extraction; hidden Markov model; recognition rate; speaker independent speech recognition; speech feature; standard deviation; uniform sub-bands; vector quantisation;
fLanguage
English
Journal_Title
Electronics Letters
Publisher
iet
ISSN
0013-5194
Type
jour
DOI
10.1049/el:19981486
Filename
739591
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