Automatic evaluation of machine translation quality using longest common subsequence and skip-bigram statistics
Article Status
Published
Authors/contributors
- Lin, Chin-Yew (Author)
- Och, Franz Josef (Author)
Title
Automatic evaluation of machine translation quality using longest common subsequence and skip-bigram statistics
Date
2004
Proceedings Title
Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics - ACL '04
Conference Name
the 42nd Annual Meeting
Place
Barcelona, Spain
Publisher
Association for Computational Linguistics
Pages
605-es
Language
en
Accessed
27/10/2023, 16:45
Library Catalogue
DOI.org (Crossref)
Extra
<AI Smry>: Two new objective automatic evaluation methods for machine translation based on longest common subsequence between a candidate translation and a set of reference translations and relaxes strict n-gram matching to skip-bigram matching are described.
Citation
Lin, C.-Y., & Och, F. J. (2004). Automatic evaluation of machine translation quality using longest common subsequence and skip-bigram statistics. Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics - ACL ’04, 605-es. https://doi.org/10.3115/1218955.1219032
Technical methods
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