Emprical study of a two-step approach to estimate translation quality

Jesús González-Rubio, J. Ramón Navarro-Cerdán, Francisco Casacuberta


Abstract
We present a method to estimate the quality of automatic translations when reference translations are not available. Quality estimation is addressed as a two-step regression problem where multiple features are combined to predict a quality score. Given a set of features, we aim at automatically extracting the variables that better explain translation quality, and use them to predict the quality score. The soundness of our approach is assessed by the encouraging results obtained in an exhaustive experimentation with several feature sets. Moreover, the studied approach is highly-scalable allowing us to employ hundreds of features to predict translation quality.
Anthology ID:
2013.iwslt-papers.5
Volume:
Proceedings of the 10th International Workshop on Spoken Language Translation: Papers
Month:
December 5-6
Year:
2013
Address:
Heidelberg, Germany
Editor:
Joy Ying Zhang
Venue:
IWSLT
SIG:
SIGSLT
Publisher:
Note:
Pages:
Language:
URL:
https://aclanthology.org/2013.iwslt-papers.5
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Cite (ACL):
Jesús González-Rubio, J. Ramón Navarro-Cerdán, and Francisco Casacuberta. 2013. Emprical study of a two-step approach to estimate translation quality. In Proceedings of the 10th International Workshop on Spoken Language Translation: Papers, Heidelberg, Germany.
Cite (Informal):
Emprical study of a two-step approach to estimate translation quality (González-Rubio et al., IWSLT 2013)
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PDF:
https://preview.aclanthology.org/add_acl24_videos/2013.iwslt-papers.5.pdf