Abstract
In this paper, we discuss techniques to combine an interlingua translation framework with phrase-based statistical methods, for translation from Chinese into English. Our goal is to achieve high-quality translation, suitable for use in language tutoring applications. We explore these ideas in the context of a flight domain, for which we have a large corpus of English queries, obtained from users interacting with a dialogue system. Our techniques exploit a pre-existing English-to-Chinese translation system to automatically produce a synthetic bilingual corpus. Several experiments were conducted combining linguistic and statistical methods, and manual evaluation was conducted for a set of 460 Chinese sentences. The best performance achieved an “adequate” or better analysis (3 or above rating) on nearly 94% of the 409 parsable subset. Using a Rover scheme to combine four systems resulted in an “adequate or better” rating for 88% of all the utterances.- Anthology ID:
- 2006.amta-papers.24
- Volume:
- Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers
- Month:
- August 8-12
- Year:
- 2006
- Address:
- Cambridge, Massachusetts, USA
- Venue:
- AMTA
- SIG:
- Publisher:
- Association for Machine Translation in the Americas
- Note:
- Pages:
- 213–222
- Language:
- URL:
- https://aclanthology.org/2006.amta-papers.24
- DOI:
- Cite (ACL):
- Stephanie Seneff, Chao Wang, and John Lee. 2006. Combining Linguistic and Statistical Methods for Bi-directional English Chinese Translation in the Flight Domain. In Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers, pages 213–222, Cambridge, Massachusetts, USA. Association for Machine Translation in the Americas.
- Cite (Informal):
- Combining Linguistic and Statistical Methods for Bi-directional English Chinese Translation in the Flight Domain (Seneff et al., AMTA 2006)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2006.amta-papers.24.pdf