DocumentCode
2267828
Title
Models and algorithms for continuous speech recognition: a brief tutorial
Author
Gopalakrishnan, P.S. ; Nahamoo, David
Author_Institution
IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
fYear
1993
fDate
16-18 Aug 1993
Firstpage
1535
Abstract
Large vocabulary continuous speech recognition presents several challenging problems. One source of complexity is the variation in the pronunciation of words arising from the phonetic context. The complexity also increases because of the large search space that continuous speech recognizers have to deal with. In this paper we discuss some methods for modeling context dependent variations in continuous speech. We describe algorithms for using the phonetic context information during recognition
Keywords
hidden Markov models; probability; search problems; speech recognition; continuous speech recognition; large vocabulary; modeling context dependent variations; phonetic context information; pronunciation variation; word lookahead scheme; Context modeling; Decision trees; Decoding; Humans; Parameter extraction; Speech recognition; Tutorial; Vector quantization; Vocabulary;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1993., Proceedings of the 36th Midwest Symposium on
Conference_Location
Detroit, MI
Print_ISBN
0-7803-1760-2
Type
conf
DOI
10.1109/MWSCAS.1993.343408
Filename
343408
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