Building Parallel Corpora from Movies

Lavecchia Caroline, Smaïli Kamel, Langlois David

Abstract

This paper proposes to use DTW to construct parallel corpora from difficult data. Parallel corpora are considered as raw material for machine translation (MT), frequently, MT systems use European or Canadian parliament corpora. In order to achieve a realistic machine translation system, we decided to use movie subtitles. These data could be considered difficult because they contain unfamiliar expressions, abbreviations, hesitations, words which do not exist in classical dictionaries (as vulgar words), etc. The obtained parallel corpora can constitute a rich resource to train decoding spontaneous speech translation system. From 40 movies, we align 43013 English subtitles with 42306 French subtitles. This leads to 37625 aligned pairs with a precision of 92, 3%.

References

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Paper Citation


in Harvard Style

Caroline L., Kamel S. and David L. (2007). Building Parallel Corpora from Movies . In Proceedings of the 4th International Workshop on Natural Language Processing and Cognitive Science - Volume 1: NLPCS, (ICEIS 2007) ISBN 978-972-8865-97-9, pages 201-210. DOI: 10.5220/0002435202010210


in Bibtex Style

@conference{nlpcs07,
author={Lavecchia Caroline and Smaïli Kamel and Langlois David},
title={Building Parallel Corpora from Movies},
booktitle={Proceedings of the 4th International Workshop on Natural Language Processing and Cognitive Science - Volume 1: NLPCS, (ICEIS 2007)},
year={2007},
pages={201-210},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002435202010210},
isbn={978-972-8865-97-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Workshop on Natural Language Processing and Cognitive Science - Volume 1: NLPCS, (ICEIS 2007)
TI - Building Parallel Corpora from Movies
SN - 978-972-8865-97-9
AU - Caroline L.
AU - Kamel S.
AU - David L.
PY - 2007
SP - 201
EP - 210
DO - 10.5220/0002435202010210