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Sentence-level quality estimation for MT system combination

Okita, Tsuyoshi, Rubino, Raphael and van Genabith, Josef orcid logoORCID: 0000-0003-1322-7944 (2012) Sentence-level quality estimation for MT system combination. In: ML4HMT-12 Workshop, 9 Dec 2012, Mumbai, India.

Abstract
This paper provides the system description of the Dublin City University system combination module for our participation in the system combination task in the Second Workshop on Applying Machine Learning Techniques to Optimize the Division of Labour in Hybrid MT (ML4HMT- 12). We incorporated a sentence-level quality score, obtained by sentence-level Quality Estimation (QE), as meta information guiding system combination. Instead of using BLEU or (minimum average) TER, we select a backbone for the confusion network using the estimated quality score. For the Spanish-English data, our strategy improved 0.89 BLEU points absolute compared to the best single score and 0.20 BLEU points absolute compared to the standard system combination strategy
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:No
Uncontrolled Keywords:Statistical Machine Translation; System Combination; Quality Estimation
Subjects:Computer Science > Machine translating
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:17673
Deposited On:19 Dec 2012 11:33 by Tsuyoshi Okita . Last Modified 19 Jan 2022 12:46
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