Abstract
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.- Anthology ID:
- W89-0213
- Volume:
- Proceedings of the First International Workshop on Parsing Technologies
- Month:
- August
- Year:
- 1989
- Address:
- Pittsburgh, Pennsylvania, USA
- Venue:
- IWPT
- SIG:
- SIGPARSE
- Publisher:
- Carnegy Mellon University
- Note:
- Pages:
- 126–131
- Language:
- URL:
- https://aclanthology.org/W89-0213
- DOI:
- Cite (ACL):
- Kenji Kita, Takeshi Kawabata, and Hiroaki Saito. 1989. Parsing Continuous Speech by HMM-LR Method. In Proceedings of the First International Workshop on Parsing Technologies, pages 126–131, Pittsburgh, Pennsylvania, USA. Carnegy Mellon University.
- Cite (Informal):
- Parsing Continuous Speech by HMM-LR Method (Kita et al., IWPT 1989)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/W89-0213.pdf