Confidence estimation for machine translation
John Blatz,Erin Fitzgerald,George Foster,Simona Gandrabur,Cyril Goutte,Alex Kulesza,Alberto Sanchis,Nicola Ueffing +7 more
- 23 Aug 2004
- pp 315-321
TL;DR: A detailed study of confidence estimation for machine translation, using data from the NIST 2003 Chinese-to-English MT evaluation to investigate various methods for determining whether MT output is correct.
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Abstract: We present a detailed study of confidence estimation for machine translation. Various methods for determining whether MT output is correct are investigated, for both whole sentences and words. Since the notion of correctness is not intuitively clear in this context, different ways of defining it are proposed. We present results on data from the NIST 2003 Chinese-to-English MT evaluation.
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Citations
METEOR: An Automatic Metric for MT Evaluation with High Levels of Correlation with Human Judgments
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- 23 Jun 2007
TL;DR: The technical details underlying the Meteor metric are recapped, the latest release includes improved metric parameters and extends the metric to support evaluation of MT output in Spanish, French and German, in addition to English.
The Meteor metric for automatic evaluation of machine translation
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TL;DR: The Meteor Automatic Metric for Machine Translation evaluation, originally developed and released in 2004, was designed with the explicit goal of producing sentence-level scores which correlate well with human judgments of translation quality.
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TL;DR: Results show that the proposed method allows obtaining good estimates and that identifying a reduced set of relevant features plays an important role in predicting the quality of sentences produced by machine translation systems when reference translations are not available.
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