Paper Info
Title
Leveraging Compounds To Improve Noun Phrase Translation From Chinese And German
Abstract
This paper presents a method to improve the translation of polysemous nouns, when a previous occurrence of the noun as the head of a compound noun phrase is available in a text. The occurrences are identified through pattern matching rules, which detect XY compounds followed closely by a potentially coreferent occurrence of Y, such as "Nordwand ... Wand". Two strategies are proposed to improve the translation of the second occurrence of Y: re-using the cached translation of Y from the XY compound, or post-editing the translation of Y using the head of the translation of XY. Experiments are performed on Chinese-to-English and German-to-French statistical machine translation, over the WIT3 and Text+Berg corpora respectively, with 261 XY/Y pairs each. The results suggest that while the overall BLEU scores increase only slightly, the translations of the targeted polysemous nouns are significantly improved.
Year
Venue
Field
2015
53RD ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS AND THE 7TH INTERNATIONAL JOINT CONFERENCE ON NATURAL LANGUAGE PROCESSING: PROCEEDINGS OF THE STUDENT RESEARCH WORKSHOP (ACL-IJCNLP 2015)
Noun phrase,Rule-based machine translation,Example-based machine translation,BLEU,Computer science,Machine translation,Noun,Speech recognition,Artificial intelligence,Natural language processing,Pattern matching,German
DocType
Volume
Citations 
Conference
P15-3
2
PageRank 
References 
Authors
0.43
10
6
Name
Order
Citations
PageRank
Xiao Pu131.45
Laura Mascarell272.61
Andrei Popescu-Belis357364.13
Mark Fishel46417.32
Ngoc-Quang Luong5438.43
Martin Volk64711.21