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