@inproceedings{corston-oliver2001a,
author = {Corston-Oliver, Simon and Gamon, Michael and Brockett, Chris},
title = {A Machine Learning Approach to the Automatic Evaluation of Machine Translation},
year = {2001},
month = {January},
abstract = {We present a machine learning approach to evaluating the well-formedness of output of a machine translation system, using classifiers that learn to distinguish human reference translations from machine translations. This approach can be used to evaluate an MT system, tracking improvements over time; to aid in the kind of failure analysis that can help guide system development; and to select among alternative output strings. The method presented is fully automated and independent of source language, target language and domain.},
publisher = {Association for Computational Linguistics},
url = {http://approjects.co.za/?big=en-us/research/publication/a-machine-learning-approach-to-the-automatic-evaluation-of-machine-translation/},
}