Rule-Based Augmentation of Training Data in Breton-French Statistical Machine Translation

3370

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nan

Abstract

This article describes an initial statistical machine translation system between Bre- ton, a Celtic language spoken in France, and French. It also describes a method for leveraging existing resources from an incomplete rule-based machine translation system to improve the coverage and trans- lation quality of the statistical system by generating expanded bilingual vocabulary lists. Results are presented which show that the use of this method improves the re- sults of the system with respect to both the baseline, and the baseline with a lemma- to-lemma bilingual lexicon. 1

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Proceedings of the 13th Annual Conference of the EAMT, pages 213–217, Barcelona, May 2009 Rule-Based Augmentation of Training Data in Breton–French Statistical Machine Translation Francis M. Tyers Dept. de Llenguatges i Sist. Inform`atics, Universitat d’Alacant E-03071 Alacant (Spain) Prompsit Language Engineering Av. St. Francesc d’Ass´ıs, 74, 1r-L E-03195 l’Altet (Spain) ftyers@prompsit.com Abstract This article describes an initial statistical machine translation system between Bre- ton, a Celtic language spoken in France, and French. It also describes a method for leveraging existing resources from an incomplete rule-based machine translation system to improve the coverage and trans- lation quality of the statistical system by generating expanded bilingual vocabulary lists. Results are presented which show that the use of this method improves the re- sults of the system with respect to both the baseline, and the baseline with a lemma- to-lemma bilingual lexicon. 1 Introduction Breton is a Celtic language of the Brythonic branch largely spoken in Brittany in the north- west of France. Historically it was spoken only in the northern part of Brittany, Breizh-Izel (Lower Brittany). This contrasts with Breizh-Uhel (Higher Brittany) which is traditionally Romance- speaking. Although some sources put the number of native speakers at between 500,000 and 600,000 (Gor- don, 2005), a more up-to-date estimate can be found from the organisation Ya d’ar brezhoneg which gives a number of 201,083 as of the 11th November 2008, and states that the number is de- creasing at a rate of at least one per hour.1 Breton is classed as a language in serious danger of ex- tinction by the UNESCO Red Book on Endangered Languages (Salminen, 1999), a situation exacer- c⃝ 2009 European Association for Machine Translation. 1http://www.yadarbrezhoneg.com/ ?article245; Accessed: 11th November, 2008 bated by the laissez-faire policies of the French state. Like other Celtic languages, Breton exhibits the phenomenon of initial consonant mutation. This occurs when the initial consonant of a word changes based on morpho-syntactic context. For example in the word tad “father”, the initial con- sonant mutates to a ‘z’ (aspirant mutation) when the word follows the possessive ma “my”, so tad is “father”, while “my father” is ma zad. As for many less-resourced language pairs, while there is little aligned bilingual text, bilin- gual lexicons are more readily available. One so- lution would be to use these bilingual lexicons within a rule-based system that makes use of the features found in the bilingual lexicon: part-of- speech, gender, number etc. to try to compensate for the lack of data with some level of generalisa- tion. Even if little parallel data is available, it is still worthwhile to compare any attempt at a more linguistically motivated system with a greater gen- eralising power with a straight-forward, state-of- the-art non-linguistic approach, such as phrase- based statistical machine translation (SMT). 2 Resources 2.1 Parallel corpora For any language pair, parallel corpora are the scarcest of all resources. In the case of a lan- guage with a small population of speakers and no official recognition, the hurdle is even greater. In contrast …

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This article describes an initial statistical machine translation system between Breton, a Celtic language spoken in France, and French. It also describes a method for leveraging existing resources from an incomplete rule-based machine translation system to improve the coverage and translation quality of the statistical system by generating expanded bilingual vocabulary lists. Results are presented which show that the use of this method improves the results of the system with respect to both the baseline, and the baseline with a lemmato-lemma bilingual lexicon. 1

Publication Details

Paper ID:
3370
Year:
2009
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan