@inproceedings{specia-etal-2010-dataset,
title = "A Dataset for Assessing Machine Translation Evaluation Metrics",
author = "Specia, Lucia and
Cancedda, Nicola and
Dymetman, Marc",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Rosner, Mike and
Tapias, Daniel",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = "2010",
address = "Valletta, Malta",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/504_Paper.pdf",
abstract = "We describe a dataset containing 16,000 translations produced by four machine translation systems and manually annotated for quality by professional translators. This dataset can be used in a range of tasks assessing machine translation evaluation metrics, from basic correlation analysis to training and test of machine learning-based metrics. By providing a standard dataset for such tasks, we hope to encourage the development of better MT evaluation metrics.",
}
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<abstract>We describe a dataset containing 16,000 translations produced by four machine translation systems and manually annotated for quality by professional translators. This dataset can be used in a range of tasks assessing machine translation evaluation metrics, from basic correlation analysis to training and test of machine learning-based metrics. By providing a standard dataset for such tasks, we hope to encourage the development of better MT evaluation metrics.</abstract>
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%0 Conference Proceedings
%T A Dataset for Assessing Machine Translation Evaluation Metrics
%A Specia, Lucia
%A Cancedda, Nicola
%A Dymetman, Marc
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Rosner, Mike
%Y Tapias, Daniel
%S Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)
%D 2010
%8 May
%I European Language Resources Association (ELRA)
%C Valletta, Malta
%F specia-etal-2010-dataset
%X We describe a dataset containing 16,000 translations produced by four machine translation systems and manually annotated for quality by professional translators. This dataset can be used in a range of tasks assessing machine translation evaluation metrics, from basic correlation analysis to training and test of machine learning-based metrics. By providing a standard dataset for such tasks, we hope to encourage the development of better MT evaluation metrics.
%U http://www.lrec-conf.org/proceedings/lrec2010/pdf/504_Paper.pdf
Markdown (Informal)
[A Dataset for Assessing Machine Translation Evaluation Metrics](http://www.lrec-conf.org/proceedings/lrec2010/pdf/504_Paper.pdf) (Specia et al., LREC 2010)
ACL