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
Link To Document :
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