| Download | - View accepted manuscript: Statistical phrase-based post-editing (PDF, 271 KiB)
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| Author | Search for: Simard, Michel1; Search for: Goutte, Cyril1; Search for: Isabelle, Pierre1 |
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| Affiliation | - National Research Council of Canada. NRC Institute for Information Technology
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| Format | Text, Article |
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| Conference | Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT 2007), April 22-27, 2007, Rochester, New York, USA |
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| Abstract | We propose to use a statistical phrase-based machine translation system in a post-editing task: the system takes as input raw machine translation output (from a commercial rule-based MT system), and produces post-edited target-language text. We report on experiments that were performed on data collected in precisely such a setting: pairs of raw MT output and their manually post-edited versions. In our evaluation, the output of our automatic post-editing (APE) system is not only better quality than the rule-based MT (both in terms of the BLEU and TER metrics), it is also better than the output of a state-of-the-art phrase-based MT System used in standalone translation mode. These results indicate that automatic post-editing constitutes a simple and efficient way of combining rule-based and statistical MT technologies. |
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| Publication date | 2007 |
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| In | |
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| Language | English |
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| NRC number | NRCC 49288 |
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| NPARC number | 5764892 |
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| Export citation | Export as RIS |
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| Report a correction | Report a correction (opens in a new tab) |
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| Record identifier | aaa8c0b3-9d7a-4db3-9b1d-c3deab67d09f |
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| Record created | 2009-03-29 |
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| Record modified | 2020-08-12 |
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