Abstract / Description of output
We present the UvA-ILLC submission of the BEER metric to WMT 14 metrics task. BEER is a sentence level metric that can incorporate a large number of features combined in a linear model. Novel contributions are (1) efficient tuning of a large number of features for maximizing correlation with human system ranking, and (2) novel features that give smoother sentence level scores.
Original language | English |
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Title of host publication | Proceedings of the Ninth Workshop on Statistical Machine Translation |
Place of Publication | Baltimore, Maryland, USA |
Publisher | Association for Computational Linguistics (ACL) |
Pages | 414-419 |
Number of pages | 6 |
DOIs | |
Publication status | Published - Jun 2014 |
Event | Ninth Workshop on Statistical Machine Translation - Baltimore, United States Duration: 26 Jun 2014 → 27 Jun 2014 http://www.statmt.org/wmt14/ |
Conference
Conference | Ninth Workshop on Statistical Machine Translation |
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Country/Territory | United States |
City | Baltimore |
Period | 26/06/14 → 27/06/14 |
Internet address |