Machine translation through clausal syntax : a statistical approach for Chinese to English

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008. === Includes bibliographical references (p. 80-82). === Language pairs such as Chinese and English with largely differing word order have proved to be one of the greatest challenges i...

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Main Author: Wheeler, Dan Lowe
Other Authors: Michael Collins.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2009
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Online Access:http://hdl.handle.net/1721.1/46535
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spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-465352019-05-02T15:48:33Z Machine translation through clausal syntax : a statistical approach for Chinese to English Incorporating syntax into machine translation : a statistical approach for Chinese to English Wheeler, Dan Lowe Michael Collins. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008. Includes bibliographical references (p. 80-82). Language pairs such as Chinese and English with largely differing word order have proved to be one of the greatest challenges in statistical machine translation. One reason is that such techniques usually work with sentences as flat strings of words, rather than explicitly attempting to parse any sort of hierarchical structural representation. Because even simple syntactic differences between languages can quickly lead to a universe of idiosyncratic surface level word reordering rules, many believe the near future of machine translation will lie heavily in syntactic modeling. The time to start may be now: advances in statistical parsing over the last decade have already started opening the door. Following the work of Cowan et al., I present a statistical tree-to-tree translation system for Chinese to English that formulates the translation step as a prediction of English clause structure from Chinese clause structure. Chinese sentences are segmented and parsed, split into clauses, and independently translated into English clauses using a discriminative feature based model. Clausal arguments, such as subject and object, are translated separately using an off-the-shelf phrase-based translator. By explicitly modeling syntax at a clausal level, but using a phrase-based (flat-sentence) method on local, reduced expressions, such as clausal arguments, I aim to address the current weakness in long-distance word reordering while still leveraging the excellent local translations that today's state of the art has to offer. by Dan Lowe Wheeler. M.Eng. 2009-08-26T16:44:27Z 2009-08-26T16:44:27Z 2008 2008 Thesis http://hdl.handle.net/1721.1/46535 416602511 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 293 p. application/pdf Massachusetts Institute of Technology
collection NDLTD
language English
format Others
sources NDLTD
topic Electrical Engineering and Computer Science.
spellingShingle Electrical Engineering and Computer Science.
Wheeler, Dan Lowe
Machine translation through clausal syntax : a statistical approach for Chinese to English
description Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008. === Includes bibliographical references (p. 80-82). === Language pairs such as Chinese and English with largely differing word order have proved to be one of the greatest challenges in statistical machine translation. One reason is that such techniques usually work with sentences as flat strings of words, rather than explicitly attempting to parse any sort of hierarchical structural representation. Because even simple syntactic differences between languages can quickly lead to a universe of idiosyncratic surface level word reordering rules, many believe the near future of machine translation will lie heavily in syntactic modeling. The time to start may be now: advances in statistical parsing over the last decade have already started opening the door. Following the work of Cowan et al., I present a statistical tree-to-tree translation system for Chinese to English that formulates the translation step as a prediction of English clause structure from Chinese clause structure. Chinese sentences are segmented and parsed, split into clauses, and independently translated into English clauses using a discriminative feature based model. Clausal arguments, such as subject and object, are translated separately using an off-the-shelf phrase-based translator. By explicitly modeling syntax at a clausal level, but using a phrase-based (flat-sentence) method on local, reduced expressions, such as clausal arguments, I aim to address the current weakness in long-distance word reordering while still leveraging the excellent local translations that today's state of the art has to offer. === by Dan Lowe Wheeler. === M.Eng.
author2 Michael Collins.
author_facet Michael Collins.
Wheeler, Dan Lowe
author Wheeler, Dan Lowe
author_sort Wheeler, Dan Lowe
title Machine translation through clausal syntax : a statistical approach for Chinese to English
title_short Machine translation through clausal syntax : a statistical approach for Chinese to English
title_full Machine translation through clausal syntax : a statistical approach for Chinese to English
title_fullStr Machine translation through clausal syntax : a statistical approach for Chinese to English
title_full_unstemmed Machine translation through clausal syntax : a statistical approach for Chinese to English
title_sort machine translation through clausal syntax : a statistical approach for chinese to english
publisher Massachusetts Institute of Technology
publishDate 2009
url http://hdl.handle.net/1721.1/46535
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