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    <abstract>This paper presents an attempt at developing a technique of acquiring translation pairs of technical terms with sufficiently high precision from parallel patent documents. The approach taken in the proposed technique is based on integrating the phrase translation table of a state-of-the-art statistical phrase-based machine translation model, and compositional translation generation based on an existing bilingual lexicon for human use. Our evaluation results clearly show that the agreement between the two individual techniques definitely contribute to improving precision of translation candidates. We then apply the Support Vector Machines (SVMs) to the task of automatically validating translation candidates in the phrase translation table. Experimental evaluation results again show that the SVMs based approach to translation candidates validation can contribute to improving the precision of translation candidates in the phrase translation table.</abstract>
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%0 Conference Proceedings
%T Integrating a Phrase-based SMT Model and a Bilingual Lexicon for Semi-Automatic Acquisition of Technical Term Translation Lexicons
%A Morishita, Yohei
%A Utsuro, Takehito
%A Yamamoto, Mikio
%S Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Research Papers
%D 2008
%8 oct 21 25
%I Association for Machine Translation in the Americas
%C Waikiki, USA
%F morishita-etal-2008-integrating
%X This paper presents an attempt at developing a technique of acquiring translation pairs of technical terms with sufficiently high precision from parallel patent documents. The approach taken in the proposed technique is based on integrating the phrase translation table of a state-of-the-art statistical phrase-based machine translation model, and compositional translation generation based on an existing bilingual lexicon for human use. Our evaluation results clearly show that the agreement between the two individual techniques definitely contribute to improving precision of translation candidates. We then apply the Support Vector Machines (SVMs) to the task of automatically validating translation candidates in the phrase translation table. Experimental evaluation results again show that the SVMs based approach to translation candidates validation can contribute to improving the precision of translation candidates in the phrase translation table.
%U https://aclanthology.org/2008.amta-papers.14
%P 153-162

Markdown (Informal)

[Integrating a Phrase-based SMT Model and a Bilingual Lexicon for Semi-Automatic Acquisition of Technical Term Translation Lexicons](https://aclanthology.org/2008.amta-papers.14) (Morishita et al., AMTA 2008)

• Integrating a Phrase-based SMT Model and a Bilingual Lexicon for Semi-Automatic Acquisition of Technical Term Translation Lexicons (Morishita et al., AMTA 2008)

ACL

• Yohei Morishita, Takehito Utsuro, and Mikio Yamamoto. 2008. Integrating a Phrase-based SMT Model and a Bilingual Lexicon for Semi-Automatic Acquisition of Technical Term Translation Lexicons. In Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Research Papers, pages 153–162, Waikiki, USA. Association for Machine Translation in the Americas.