Parmesan: Meteor without Paraphrases with Paraphrased References
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F14%3A10289359" target="_blank" >RIV/00216208:11320/14:10289359 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Parmesan: Meteor without Paraphrases with Paraphrased References
Original language description
This paper describes Parmesan, our submission to the 2014 Workshop on Statistical Machine Translation (WMT) metrics task for evaluation English-to-Czech translation. We show that the Czech Meteor Paraphrase tables are so noisy that they actually can harmthe performance of the metric. However, they can be very useful after extensive filtering in targeted paraphrasing of Czech reference sentences prior to the evaluation. Parmesan first performs targeted paraphrasing of reference sentences, then it computes the Meteor score using only the exact match on~these new reference sentences. It shows significantly higher correlation with human judgment than Meteor on the WMT12 and WMT13 data.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the Ninth Workshop on Statistical Machine Translation
ISBN
978-1-941643-17-4
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
355-361
Publisher name
Association for Computational Linguistics
Place of publication
Baltimore, MD, USA
Event location
Baltimore, MD, USA
Event date
Jun 26, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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