Takeshi Kawabata


Understanding Unsegmented User Utterances in Real-Time Spoken Dialogue Systems
Mikio Nakano | Noboru Miyazaki | Jun-ichi Hirasawa | Kohji Dohsaka | Takeshi Kawabata
Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics


Discourse Markers in Spontaneous Dialogue: A Corpus based study of Japanese and English
Masahito Kawamori | Takeshi Kawabata | Akira Shimazu
Discourse Relations and Discourse Markers


A Phonological Study on Japanese Discourse Markers
Masahito Kawamori | Akira Shimazu | Takeshi Kawabata
Proceedings of the 11th Pacific Asia Conference on Language, Information and Computation


Neural Network Approach to Word Category Prediction for English Texts
Masami Nakamura | Katsuteru Maruyama | Takeshi Kawabata | Kiyohiro Shikano
COLING 1990 Volume 3: Papers presented to the 13th International Conference on Computational Linguistics


Parsing Continuous Speech by HMM-LR Method
Kenji Kita | Takeshi Kawabata | Hiroaki Saito
Proceedings of the First International Workshop on Parsing Technologies

This paper describes a speech parsing method called HMM-LR. In HMM-LR, an LR parsing table is used to predict phones in speech input, and the system drives an HMM-based speech recognizer directly without any intervening structures such as a phone lattice. Very accurate, efficient speech parsing is achieved through the integrated processes of speech recognition and language analysis. The HMM-LR m ethod is applied to large-vocabulary speaker-dependent Japanese phrase recognition. The recognition rate is 87.1% for the top candidates and 97.7% for the five best candidates.