DocumentCode :
2998604
Title :
Acoustic Markov models used in the Tangora speech recognition system
Author :
Bahl, L.R. ; Brown, P.F. ; de Souza, P.V. ; Picheny, M.A.
Author_Institution :
IBM Thomas J. Watson Res. Center, Yorktown Heights, NY
fYear :
1988
fDate :
11-14 Apr 1988
Firstpage :
497
Abstract :
The Speech Recognition Group at IBM Research has developed a real-time, isolated-word speech recognizer called Tangora, which accepts natural English sentences drawn from a vocabulary of 20000 words. Despite its large vocabulary, the Tangora recognizer requires only about 20 minutes of speech from each new user for training purposes. The accuracy of the system and its ease of training are largely attributable to the use of hidden Markov models in its acoustic match component. An automatic technique for constructing Markov word models is described and results are included of experiments with speaker-dependent and speaker-independent models on several isolated-word recognition tasks
Keywords :
Markov processes; acoustic signal processing; speech analysis and processing; speech recognition; English sentences; IBM Research; Markov word models; Tangora speech recognition system; acoustic Markov models; acoustic match component; hidden Markov models; isolated-word speech recognizer; real-time speech recogniser; speaker-dependent models; speaker-independent models; training; vocabulary; Automatic speech recognition; Degradation; Error analysis; Heart; Hidden Markov models; Lead; Real time systems; Speech recognition; Speech synthesis; Vocabulary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on
Conference_Location :
New York, NY
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.1988.196628
Filename :
196628
Link To Document :
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