Using a Bilingual Context in Word-Based Statistical Machine Translation

Christoph Schmidt; David Vilar; Hermann Ney

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Paper

Using a Bilingual Context in Word-Based Statistical Machine Translation

In Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems - Volume 0ICEIS, 144-153, 2008 , Barcelona, Spain

Authors: Christoph Schmidt ; David Vilar and Hermann Ney

Affiliation: Chair of Computer Science 6, RWTH Aachen University, Germany

Abstract: In statistical machine translation, phrase-based translation (PBT) models lead to a significantly better translation quality over single-word-based (SWB) models. PBT models translate whole phrases, thus considering the context in which a word occurs. In this work, we propose a model which further extends this context beyond phrase boundaries. The model is compared to a PBT model on the IWSLT 2007 corpus. To profit from the respective advantages of both models, we use a model combination, which results in an improvement in translation quality on the examined corpus.

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Paper citation in several formats:

Schmidt, C.; Vilar, D. and Ney, H. (2008). Using a Bilingual Context in Word-Based Statistical Machine Translation. In Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems (ICEIS 2008) - PRIS; ISBN 978-989-8111-42-5, SciTePress, pages 144-153. DOI: 10.5220/0001742201440153

@conference{pris08,
author={Christoph Schmidt. and David Vilar. and Hermann Ney.},
title={Using a Bilingual Context in Word-Based Statistical Machine Translation},
booktitle={Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems (ICEIS 2008) - PRIS},
year={2008},
pages={144-153},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001742201440153},
isbn={978-989-8111-42-5},
}

TY - CONF

JO - Proceedings of the 8th International Workshop on Pattern Recognition in Information Systems (ICEIS 2008) - PRIS
TI - Using a Bilingual Context in Word-Based Statistical Machine Translation
SN - 978-989-8111-42-5
AU - Schmidt, C.
AU - Vilar, D.
AU - Ney, H.
PY - 2008
SP - 144
EP - 153
DO - 10.5220/0001742201440153
PB - SciTePress