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Integrating Specialized Bilingual Lexicons of Multiword Expressions for Domain Adaptation in Statistical Machine Translation

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Computational Linguistics (PACLING 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 781))

Abstract

Domain adaptation consists in adapting Machine Translation (MT) systems designed for one domain to work in another. Multiword expressions generally characterize specific-domains vocabularies. Translating multiword expressions is a challenge for current Statistical Machine Translation (SMT) systems because corpus-based approaches are effective only when large amounts of parallel corpora are available. However, parallel corpora are only available for a limited number of language pairs and domains, and the process of building corpora for several language pairs and domains is time consuming and expensive. This paper describes an experimental evaluation of the impact of using a specialized bilingual lexicon of multiword expressions in order to obtain better domain adaptation for the state of the art statistical machine translation system Moses. Our study concerns the English-French language pair and two kinds of texts: in-domain texts from Europarl (European Parliament Proceedings) and out-of-domain texts from Emea (European Medicines Agency Documents). We introduce three methods to integrate extracted bilingual multiword expressions in Moses. We experimentally show that integrating specialized bilingual lexicons of multiword expressions improve translation quality of Moses for both in-domain and out-of-domain texts.

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Notes

  1. 1.

    http://www.statmt.org/moses/.

  2. 2.

    http://www.statmt.org/moses/giza/GIZA++.html.

  3. 3.

    http://www.statmt.org/moses/?n=Moses.FactoredModels.

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Acknowledgments

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 700381.

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Authors and Affiliations

  1. CEA, LIST, Vision and Content Engineering Laboratory, 91191, Gif-sur-Yvette, France

    Nasredine Semmar & Meriama Laib

Authors
  1. Nasredine Semmar
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  2. Meriama Laib
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Corresponding author

Correspondence to Nasredine Semmar .

Editor information

Editors and Affiliations

  1. Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan

    Kôiti Hasida

  2. Natural Language Processing Lab, University of Computer Studies, Yangon, Yangon, Myanmar

    Win Pa Pa

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Semmar, N., Laib, M. (2018). Integrating Specialized Bilingual Lexicons of Multiword Expressions for Domain Adaptation in Statistical Machine Translation. In: Hasida, K., Pa, W. (eds) Computational Linguistics. PACLING 2017. Communications in Computer and Information Science, vol 781. Springer, Singapore. https://doi.org/10.1007/978-981-10-8438-6_9

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  • DOI: https://doi.org/10.1007/978-981-10-8438-6_9

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8437-9

  • Online ISBN: 978-981-10-8438-6

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