A Relationship: Word Alignment, Phrase Table, and Translation Quality
In the last years, researchers conducted several studies to evaluate the machine translation quality based on the relationship between word alignments and phrase table. However, existing methods usually employ ad-hoc heuristics without theoretical support. So far, there is no discussion from the asp...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/438106 |
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| author | Liang Tian Derek F. Wong Lidia S. Chao Francisco Oliveira |
| author_facet | Liang Tian Derek F. Wong Lidia S. Chao Francisco Oliveira |
| author_sort | Liang Tian |
| collection | DOAJ |
| description | In the last years, researchers conducted several studies to evaluate the machine translation quality based on the relationship between word alignments and phrase table. However, existing methods usually employ ad-hoc heuristics without theoretical support. So far, there is no discussion from the aspect of providing a formula to describe the relationship among word alignments, phrase table, and machine translation performance. In this paper, on one hand, we focus on formulating such a relationship for estimating the size of extracted phrase pairs given one or more word alignment points. On the other hand, a corpus-motivated pruning technique is proposed to prune the default large phrase table. Experiment proves that the deduced formula is feasible, which not only can be used to predict the size of the phrase table, but also can be a valuable reference for investigating the relationship between the translation performance and phrase tables based on different links of word alignment. The corpus-motivated pruning results show that nearly 98% of phrases can be reduced without any significant loss in translation quality. |
| format | Article |
| id | doaj-art-ab973ba83ddb49b5b0c8a31f5c888f95 |
| institution | OA Journals |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-ab973ba83ddb49b5b0c8a31f5c888f952025-08-20T02:20:12ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/438106438106A Relationship: Word Alignment, Phrase Table, and Translation QualityLiang Tian0Derek F. Wong1Lidia S. Chao2Francisco Oliveira3Natural Language Processing & Portuguese-Chinese Machine Translation Laboratory, Department of Computer and Information Science, University of Macau, MacauNatural Language Processing & Portuguese-Chinese Machine Translation Laboratory, Department of Computer and Information Science, University of Macau, MacauNatural Language Processing & Portuguese-Chinese Machine Translation Laboratory, Department of Computer and Information Science, University of Macau, MacauNatural Language Processing & Portuguese-Chinese Machine Translation Laboratory, Department of Computer and Information Science, University of Macau, MacauIn the last years, researchers conducted several studies to evaluate the machine translation quality based on the relationship between word alignments and phrase table. However, existing methods usually employ ad-hoc heuristics without theoretical support. So far, there is no discussion from the aspect of providing a formula to describe the relationship among word alignments, phrase table, and machine translation performance. In this paper, on one hand, we focus on formulating such a relationship for estimating the size of extracted phrase pairs given one or more word alignment points. On the other hand, a corpus-motivated pruning technique is proposed to prune the default large phrase table. Experiment proves that the deduced formula is feasible, which not only can be used to predict the size of the phrase table, but also can be a valuable reference for investigating the relationship between the translation performance and phrase tables based on different links of word alignment. The corpus-motivated pruning results show that nearly 98% of phrases can be reduced without any significant loss in translation quality.http://dx.doi.org/10.1155/2014/438106 |
| spellingShingle | Liang Tian Derek F. Wong Lidia S. Chao Francisco Oliveira A Relationship: Word Alignment, Phrase Table, and Translation Quality The Scientific World Journal |
| title | A Relationship: Word Alignment, Phrase Table, and Translation Quality |
| title_full | A Relationship: Word Alignment, Phrase Table, and Translation Quality |
| title_fullStr | A Relationship: Word Alignment, Phrase Table, and Translation Quality |
| title_full_unstemmed | A Relationship: Word Alignment, Phrase Table, and Translation Quality |
| title_short | A Relationship: Word Alignment, Phrase Table, and Translation Quality |
| title_sort | relationship word alignment phrase table and translation quality |
| url | http://dx.doi.org/10.1155/2014/438106 |
| work_keys_str_mv | AT liangtian arelationshipwordalignmentphrasetableandtranslationquality AT derekfwong arelationshipwordalignmentphrasetableandtranslationquality AT lidiaschao arelationshipwordalignmentphrasetableandtranslationquality AT franciscooliveira arelationshipwordalignmentphrasetableandtranslationquality AT liangtian relationshipwordalignmentphrasetableandtranslationquality AT derekfwong relationshipwordalignmentphrasetableandtranslationquality AT lidiaschao relationshipwordalignmentphrasetableandtranslationquality AT franciscooliveira relationshipwordalignmentphrasetableandtranslationquality |