@inproceedings{chinea-rios-etal-2014-online,
title = "Online optimisation of log-linear weights in interactive machine translation",
author = "Chinea Rios, Mara and
Sanchis-Trilles, Germ{\'a}n and
Ortiz-Mart{\'\i}nez, Daniel and
Casacuberta, Francisco",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/848_Paper.pdf",
pages = "3556--3559",
abstract = "Whenever the quality provided by a machine translation system is not enough, a human expert is required to correct the sentences provided by the machine translation system. In such a setup, it is crucial that the system is able to learn from the errors that have already been corrected. In this paper, we analyse the applicability of discriminative ridge regression for learning the log-linear weights of a state-of-the-art machine translation system underlying an interactive machine translation framework, with encouraging results.",
}
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%0 Conference Proceedings
%T Online optimisation of log-linear weights in interactive machine translation
%A Chinea Rios, Mara
%A Sanchis-Trilles, Germán
%A Ortiz-Martínez, Daniel
%A Casacuberta, Francisco
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F chinea-rios-etal-2014-online
%X Whenever the quality provided by a machine translation system is not enough, a human expert is required to correct the sentences provided by the machine translation system. In such a setup, it is crucial that the system is able to learn from the errors that have already been corrected. In this paper, we analyse the applicability of discriminative ridge regression for learning the log-linear weights of a state-of-the-art machine translation system underlying an interactive machine translation framework, with encouraging results.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/848_Paper.pdf
%P 3556-3559
Markdown (Informal)
[Online optimisation of log-linear weights in interactive machine translation](http://www.lrec-conf.org/proceedings/lrec2014/pdf/848_Paper.pdf) (Chinea Rios et al., LREC 2014)
ACL