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