Classification approach to word selection in machine translation

Hyo-Kyung Lee


Abstract
We present a classification approach to building a English-Korean machine translation (MT) system. We attempt to build a word-based MT system from scratch using a set of parallel documents, online dictionary queries, and monolingual documents on the web. In our approach, MT problem is decomposed into two sub-problems — word selection problem and word ordering problem of the selected words. In this paper, we will focus on the word selection problem and discuss some preliminary results.
Anthology ID:
2002.amta-papers.12
Volume:
Proceedings of the 5th Conference of the Association for Machine Translation in the Americas: Technical Papers
Month:
October 8-12
Year:
2002
Address:
Tiburon, USA
Venue:
AMTA
SIG:
Publisher:
Springer
Note:
Pages:
114–123
Language:
URL:
https://link.springer.com/chapter/10.1007/3-540-45820-4_12
DOI:
Bibkey:
Cite (ACL):
Hyo-Kyung Lee. 2002. Classification approach to word selection in machine translation. In Proceedings of the 5th Conference of the Association for Machine Translation in the Americas: Technical Papers, pages 114–123, Tiburon, USA. Springer.
Cite (Informal):
Classification approach to word selection in machine translation (Lee, AMTA 2002)
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PDF:
https://link.springer.com/chapter/10.1007/3-540-45820-4_12