English-French Verb Phrase Alignment in Europarl for Tense Translation Modeling

Sharid Loáiciga, Thomas Meyer, Andrei Popescu-Belis

Abstract
This paper presents a method for verb phrase (VP) alignment in an English-French parallel corpus and its use for improving statistical machine translation (SMT) of verb tenses. The method starts from automatic word alignment performed with GIZA++, and relies on a POS tagger and a parser, in combination with several heuristics, in order to identify non-contiguous components of VPs, and to label the aligned VPs with their tense and voice on each side. This procedure is applied to the Europarl corpus, leading to the creation of a smaller, high-precision parallel corpus with about 320,000 pairs of finite VPs, which is made publicly available. This resource is used to train a tense predictor for translation from English into French, based on a large number of surface features. Three MT systems are compared: (1) a baseline phrase-based SMT; (2) a tense-aware SMT system using the above predictions within a factored translation model; and (3) a system using oracle predictions from the aligned VPs. For several tenses, such as the French “imparfait”, the tense-aware SMT system improves significantly over the baseline and is closer to the oracle system.
Anthology ID:
L14-1205
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
674–681
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/205_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Sharid Loáiciga, Thomas Meyer, and Andrei Popescu-Belis. 2014. English-French Verb Phrase Alignment in Europarl for Tense Translation Modeling. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 674–681, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
English-French Verb Phrase Alignment in Europarl for Tense Translation Modeling (Loáiciga et al., LREC 2014)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/205_Paper.pdf
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