Abstract
Translating between dissimilar languages requires an account of the use of divergent word orders when expressing the same semantic content. Reordering poses a serious problem for statistical machine translation systems and has generated a considerable body of research aimed at meeting its challenges. Direct evaluation of reordering requires automatic metrics that explicitly measure the quality of word order choices in translations. Current metrics, such as BLEU, only evaluate reordering indirectly. We analyse the ability of current metrics to capture reordering performance. We then introduce permutation distance metrics as a direct method for measuring word order similarity between translations and reference sentences. By correlating all metrics with a novel method for eliciting human judgements of reordering quality, we show that current metrics are largely influenced by lexical choice, and that they are not able to distinguish between different reordering scenarios. Also, we show that permutation distance metrics correlate very well with human judgements, and are impervious to lexical differences.
Similar content being viewed by others
References
Birch A, Osborne M, Koehn P (2008) Predicting success in machine translation. In: Proceedings of the empirical methods in natural language processing
Callison-Burch C, Osborne M, Koehn P (2006) Re-evaluation the role of BLEU in machine translation research. In: Proceedings of EMNLP
Callison-Burch C, Fordyce C, Koehn P, Monz C, Schroeder J (2007) (Meta-) evaluation of machine translation. In: Proceedings of the second workshop on statistical machine translation. Prague, Czech Republic, pp 136–158
Callison-Burch C, Fordyce C, Koehn P, Monz C, Schroeder J (2008) Further meta-evaluation of machine translation. In: Proceedings of the third workshop on statistical machine translation. Columbus, OH, pp 70–106
Callison-Burch C, Koehn P, Monz C, Schroeder J (2009) Findings of the 2009 workshop on statistical machine translation. In: Proceedings of the fourth workshop on statistical machine translation. Athens, Greece, pp 1–28
Giménez J, Màrquez L (2007) Linguistic features for automatic evaluation of heterogenous MT systems. In: ACL workshop on statistical machine translation
Hirschberg D (1975) A linear space algorithm for computing maximal common subsequences. In: Communications of the ACM, pp 341–343
Kendall M, Dickinson Gibbons J (1990) Rank correlation methods. Oxford University Press, New York
Koehn P, Hoang H, Birch A, Callison-Burch C, Federico M, Bertoldi N, Cowan B, Shen W, Moran C, Zens R, Dyer C, Bojar O, Constantin A, Herbst E (2007) Moses: open source toolkit for statistical machine translation. In: Proceedings of the association for computational linguistics companion demo and poster sessions, Prague, Czech Republic, pp 177–180
Lapata M (2003) Probabilistic text structuring: experiments with sentence ordering. Comput Linguist 29(2): 263–317
Lapata M (2006) Automatic evaluation of information ordering: Kendall’s Tau. Comput Linguist 32(4): 471–484
Lavie A, Agarwal A (2007) METEOR: an automatic metric for MT evaluation with high levels of correlation with human judgments. In: Proceedings of the workshop on statistical machine translation at the meeting of the association for computational linguistics (ACL-2007), pp 228–231
Liang P, Taskar B, Klein D (2006) Alignment by agreement. In: Proceedings of the human language technology conference of NAAC, pp 104–111
Lin C-Y, Och F (2004) Orange: a method for evaluating automatic evaluation metrics for machine translation. In: Proceedings of the conference on computational linguistics, 501 pp
Padó S, Galley M, Manning CD, Jurafsky D (2009) Textual entailment features for machine translation evaluation. In: the EACL workshop on machine translation (WMT)
Papineni K, Roukos S, Ward T, Zhu W-J (2002) BLEU: a method for automatic evaluation of machine translation. In: Proceedings of the association for computational linguistics, Philadelphia, USA, pp 311–318
Ronald S (1998) More distance functions for order-based encodings. In: the IEEE conference on evolutionary computation, pp 558–563
Snover M, Dorr B, Schwartz R, Micciulla L, Makhoul J (2006) A study of translation edit rate with targeted human annotation. In: AMTA
Ulam S (1972) Some ideas and prospects in biomathematics. In: Annual review of biophysics and bioengineering, pp 277–292
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Birch, A., Osborne, M. & Blunsom, P. Metrics for MT evaluation: evaluating reordering. Machine Translation 24, 15–26 (2010). https://doi.org/10.1007/s10590-009-9066-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10590-009-9066-5