DocumentCode :
1815375
Title :
The application of optimization in feature extraction of speech recognition
Author :
Gu, Liang ; Liu, RenSheng
Author_Institution :
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
Volume :
1
fYear :
1996
fDate :
14-18 Oct 1996
Firstpage :
745
Abstract :
The speech recognition feature extraction methods used presently are not optimal when they are applied to a specific environment and recognition task. To deal with this problem, the new concepts of regional characteristic and trace characteristic are proposed, accompanied by the definition of the new parameter of regional resolution in the speech feature vector space. Under these concepts, optimization is introduced to turn the previous non-optimal, universal feature extraction method into a new optimal, task-dependent and environment-dependent one, which will improve the speech recognition results without changing the substructure of the original method or increasing the computational complexity
Keywords :
feature extraction; optimisation; signal resolution; speech processing; speech recognition; computational complexity; environment dependent method; feature extraction; optimal task dependent method; optimization; regional characteristic; regional resolution; speech feature vector space; speech recognition; trace characteristic; universal feature extraction method; Cepstrum; Feature extraction; Filter bank; Hidden Markov models; Information filtering; Linear predictive coding; Optimization methods; Pattern recognition; Speech processing; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, 1996., 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-2912-0
Type :
conf
DOI :
10.1109/ICSIGP.1996.567370
Filename :
567370
Link To Document :
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