ATR HMM-LR continuous speech recognition system

Author

Hanazawa, Toshiyuki ; Kita, Kenji ; Nakamura, Satoshi ; Kawabata, Takeshi ; Shikano, Kiyohiro

Author_Institution

ATR Interpreting Telephony Res. Lab., Kyoto, Japan

fYear

1990

fDate

3-6 Apr 1990

Firstpage

53

Abstract

An improvement of the hidden Markov model (HMM) LR continuous-speech recognizer using multiple codebooks, HMM state duration control and fuzzy vector quantization is described. The system recognizes Japanese phrases (Bunsetsu) according to a context-free grammar including 1035 words. In speaker-dependent conditions, a phrase recognition rate of 88.4% (99.0% for the top five candidates) was attained. The system was tested with speaker-adaptation based on a codebook mapping algorithm. An average speaker-adapted phrase recognition rate of 81.6% (98.8% for the top five candidates) was attained

Keywords

knowledge based systems; speech analysis and processing; speech recognition; Bunsetsu; HMM state duration control; Japanese phrases; codebook mapping algorithm; context-free grammar; continuous speech recognition system; fuzzy vector quantization; hidden Markov model; multiple codebooks; phrase recognition rate; speaker-adaptation; speaker-dependent conditions; Control systems; Fuzzy control; Fuzzy systems; Hidden Markov models; Laboratories; Loudspeakers; Power system modeling; Speech recognition; System testing; Telephony; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on

Conference_Location

Albuquerque, NM

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1990.115535

Filename

115535