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Dependency relations as source context in phrase-based SMT

Haque, Rejwanul orcid logoORCID: 0000-0003-1680-0099, Naskar, Sudip Kumar, van den Bosch, Antal and Way, Andy orcid logoORCID: 0000-0001-5736-5930 (2009) Dependency relations as source context in phrase-based SMT. In: PACLIC 23 - the 23rd Pacific Asia Conference on Language, Information and Computation, 3-5 December 2009, Hong Kong.

The Phrase-Based Statistical Machine Translation (PB-SMT) model has recently begun to include source context modeling, under the assumption that the proper lexical choice of an ambiguous word can be determined from the context in which it appears. Various types of lexical and syntactic features such as words, parts-of-speech, and supertags have been explored as effective source context in SMT. In this paper, we show that position-independent syntactic dependency relations of the head of a source phrase can be modeled as useful source context to improve target phrase selection and thereby improve overall performance of PB-SMT. On a Dutch—English translation task, by combining dependency relations and syntactic contextual features (part-of-speech), we achieved a 1.0 BLEU (Papineni et al., 2002) point improvement (3.1% relative) over the baseline.
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:phrase-based SMT; syntactic dependencies; memory-based learning;
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:Research Institutes and Centres > Centre for Next Generation Localisation (CNGL)
Research Institutes and Centres > National Centre for Language Technology (NCLT)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Official URL:http://paclic23.ctl.cityu.edu.hk/PACLIC23_index.ht...
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:15174
Deposited On:15 Feb 2010 14:48 by DORAS Administrator . Last Modified 13 Aug 2020 16:03

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