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Exploiting unbalanced specialized comparable corpora for bilingual lexicon extraction†

Published online by Cambridge University Press:  15 June 2016

EMMANUEL MORIN  and
AMIR HAZEM
EMMANUEL MORIN
Affiliation:
Université de Nantes, LINA UMR CNRS 6241, 2 rue de la houssinière, BP 92208, 44322 Nantes Cedex 03, France e-mails: [email protected], [email protected]
AMIR HAZEM
Affiliation:
Université de Nantes, LINA UMR CNRS 6241, 2 rue de la houssinière, BP 92208, 44322 Nantes Cedex 03, France e-mails: [email protected], [email protected]
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Abstract

The main work in bilingual lexicon extraction from comparable corpora is based on the implicit hypothesis that corpora are balanced in terms of size. However, the historical context-based projection method is relatively insensitive to the size of each part of the comparable corpus. Within this context, we have carried out a study on the influence of unbalanced specialized comparable corpora and on the quality of bilingual terminology extraction by doing different experiments. Moreover, we have introduced a strategy into the context-based projection method to re-estimate word co-occurrence observations. This is done by using smoothing or prediction techniques that boost the observations of word co-occurrences which are mainly useful for the smallest part of an unbalanced comparable corpus. Our results show that the use of unbalanced specialized comparable corpora results in a significant improvement in the quality of extracted lexicons.

Type
Articles
Information
Natural Language Engineering , Volume 22 , Issue 4: Machine Translation Using Comparable Corpora , July 2016 , pp. 575 - 601
Copyright
Copyright © Cambridge University Press 2016 

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Footnotes

†

We thank the two anonymous reviewers whose comments and suggestions helped improve and clarify this manuscript. This work is supported by the French National Research Agency under grant ANR-12-CORD-0020.

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