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Extrinsic evaluation of sentence alignment systems


Abdul-Rauf, Sadaf; Fishel, Mark; Lambert, Patrik; Noubours, Sandra; Sennrich, Rico (2012). Extrinsic evaluation of sentence alignment systems. In: Workshop on Creating Cross-language Resources for Disconnected Languages and Styles, Istanbul, 27 May 2012, 6-10.

Abstract

Parallel corpora are usually a collection of documents which are translations of each other. To be useful in NLP applications such as word alignment or machine translation, they first have to be aligned at the sentence level. This paper is a user study briefly reviewing several sentence aligners and evaluating them based on the performance achieved by the SMT systems trained on their output. We conducted experiments on two language pairs and showed that using a more advanced sentence alignment algorithm may yield gains of 0.5 to 1 BLEU points.

Abstract

Parallel corpora are usually a collection of documents which are translations of each other. To be useful in NLP applications such as word alignment or machine translation, they first have to be aligned at the sentence level. This paper is a user study briefly reviewing several sentence aligners and evaluating them based on the performance achieved by the SMT systems trained on their output. We conducted experiments on two language pairs and showed that using a more advanced sentence alignment algorithm may yield gains of 0.5 to 1 BLEU points.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Language:English
Event End Date:27 May 2012
Deposited On:04 Jun 2012 09:20
Last Modified:03 Aug 2021 15:18
OA Status:Green
Free access at:Official URL. An embargo period may apply.
Official URL:http://www.lrec-conf.org/proceedings/lrec2012/workshops/26.Credislas-Proceedings.pdf
Related URLs:http://www-lium.univ-lemans.fr/credislas2012/index.php
  • Content: Accepted Version