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METEOR-Hindi : Automatic MT Evaluation Metric for Hindi as a Target LanguageAuthors: Ankush Gupta,Sriram Venkatapathy,Rajeev Sangal Conference: ICON-2010: 8th International Conference on Natural Language Processing (ICON-2010 2010) Date: 2010-12-08 Report no: IIIT/TR/2010/188 AbstractBLEU (Papineni et al., 2002) is a widely used metric for machine translation evaluation. However, it fails to rate translations correctly for target languages that are morphologically rich and that have relatively free word order such as Hindi (Ramanathan et al., 2007). In this paper, we present METEOR-Hindi, an automatic evaluation metric for a machine translation system where the target language is Hindi. METEOR-Hindi is a modified version of the metric METEOR, containing features specific to Hindi. We make appropriate changes to METEOR’s alignment algorithm and the scoring technique. In our experiments, we observed that METEOR-Hindi achieved high correlation of 0.703 with human judgments significantly outperforming BLEU that had a correlation of only 0.271. Full paper: pdf Centre for Language Technologies Research Centre |
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