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
Proceedings Title
Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics - ACL '04
Conference Name
the 42nd Annual Meeting
Publisher
Association for Computational Linguistics
Place
Barcelona, Spain
Date
2004
Pages
605-es
Citation Key
lin2004
Accessed
27/10/2023, 16:45
Language
en
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.
<标题>: 使用最长公共子序列和跳跃二元统计进行机器翻译质量的自动评估
Read_Status: New
Read_Status_Date: 2026-01-26T11:33:53.530Z
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
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