Solutions to problems inherent in spoken-language translation: the ATR-MATRIX approach
Eiichiro Sumita, Setsuo Yamada, Kazuhide Yamamoto, Michael Paul, Hideki Kashioka, Kai Ishikawa, Satoshi Shirai
Abstract
ATR has built a multi-language speech translation system called ATR-MATRIX. It consists of a spoken-language translation subsystem, which is the focus of this paper, together with a highly accurate speech recognition subsystem and a high-definition speech synthesis subsystem. This paper gives a road map of solutions to the problems inherent in spoken-language translation. Spoken-language translation systems need to tackle difficult problems such as ungrammaticality. contextual phenomena, speech recognition errors, and the high-speeds required for real-time use. We have made great strides towards solving these problems in recent years. Our approach mainly uses an example-based translation model called TDMT. We have added the use of extra-linguistic information, a decision tree learning mechanism, and methods dealing with recognition errors.- Anthology ID:
- 1999.mtsummit-1.34
- Volume:
- Proceedings of Machine Translation Summit VII
- Month:
- September 13-17
- Year:
- 1999
- Address:
- Singapore, Singapore
- Venue:
- MTSummit
- SIG:
- Publisher:
- Note:
- Pages:
- 229–235
- Language:
- URL:
- https://preview.aclanthology.org/remove-affiliations/1999.mtsummit-1.34/
- DOI:
- Cite (ACL):
- Eiichiro Sumita, Setsuo Yamada, Kazuhide Yamamoto, Michael Paul, Hideki Kashioka, Kai Ishikawa, and Satoshi Shirai. 1999. Solutions to problems inherent in spoken-language translation: the ATR-MATRIX approach. In Proceedings of Machine Translation Summit VII, pages 229–235, Singapore, Singapore.
- Cite (Informal):
- Solutions to problems inherent in spoken-language translation: the ATR-MATRIX approach (Sumita et al., MTSummit 1999)
- PDF:
- https://preview.aclanthology.org/remove-affiliations/1999.mtsummit-1.34.pdf