METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments

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METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments (2005)

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by Alon Lavie , Abhaya Agarwal

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BibTeX

@INPROCEEDINGS{Lavie05meteor:an,
    author = {Alon Lavie and Abhaya Agarwal},
    title = {METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments},
    booktitle = {},
    year = {2005},
    pages = {65--72}
}

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Abstract

Meteor is an automatic metric for Machine Translation evaluation which has been demonstrated to have high levels of correlation with human judgments of translation quality, significantly outperforming the more commonly used Bleu metric. It is one of several automatic metrics used in this year’s shared task within the ACL WMT-07 workshop. This paper recaps the technical details underlying the metric and describes recent improvements in the metric. 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. 1

Keyphrases

human judgment automatic metric improved correlation mt evaluation improved metric parameter mt output translation quality several automatic metric technical detail high level acl wmt-07 workshop machine translation evaluation describes recent improvement

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