DocumentCode
1924254
Title
Discriminative analysis of distortion sequences in speech recognition
Author
Chang, Pao-Chung ; Chen, Sin-Horng ; Juang, Biing-hwang
Author_Institution
Telecommun. Lab., Minist. of Commun., Taiwan
fYear
1991
fDate
14-17 Apr 1991
Firstpage
549
Abstract
The authors suggest a linear discriminant function to complete the distance score instead of a conventional average distance. Several discriminative algorithms are proposed to learn the discriminant function. These include one heuristic method, two methods based on the error propagation algorithm, and one method based on the generalized probabilistic descent (GPD) algorithm. The authors study these methods in a speaker-independent speech recognition task involving utterances of the highly confusable English E-set. The results show that the best performance is obtained by using the GPD method, which achieved a 78.1% accuracy, compared to 67.6% with the traditional average method
Keywords
probability; speech recognition; English E-set; discriminative algorithms; distance score; error propagation algorithm; generalized probabilistic descent; heuristic method; linear discriminant function; recognition accuracy; speaker-independent speech recognition; Distortion measurement; Dynamic programming; Heuristic algorithms; Hidden Markov models; Pattern recognition; Performance analysis; Speech analysis; Speech recognition; Timing; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on
Conference_Location
Toronto, Ont.
ISSN
1520-6149
Print_ISBN
0-7803-0003-3
Type
conf
DOI
10.1109/ICASSP.1991.150398
Filename
150398
Link To Document