Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

Significance tests of automatic machine translation evaluation metrics

  • Published:
Machine Translation

Abstract

Automatic evaluation metrics for Machine Translation (MT) systems, such as BLEU, METEOR and the related NIST metric, are becoming increasingly important in MT research and development. This paper presents a significance test-driven comparison of n-gram-based automatic MT evaluation metrics. Statistical significance tests use bootstrapping methods to estimate the reliability of automatic machine translation evaluations. Based on this reliability estimation, we study the characteristics of different MT evaluation metrics and how to construct reliable and efficient evaluation suites.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  • Amigó E, Gonzalo J, Peñas A, Verdejo F (2005) QARLA: a framework for the evaluation of text summarization systems. In: ACL ’05: Proceedings of the 43rd annual meeting on association for computational linguistics. Association for Computational Linguistics, Morristown, NJ, USA, pp 280–289

  • Amigó E, Giménez J, Gonzalo J, Màrquez L (2006) MT evaluation: human-like vs. human acceptable. In: Proceedings of the COLING/ACL on main conference poster sessions. Association for Computational Linguistics, Morristown, NJ, USA, pp 17–24

  • Banerjee S, Lavie A (2005) METEOR: an automatic metric for MT evaluation with improved correlation with human judgments’. In: Proceedings of the ACL workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization. Association for Computational Linguistics, Ann Arbor, Michigan, pp 65–72

  • Bisani M, Ney H (2004) Bootstrap estimates for confidence intervals in ASR performance evaluation. In: Proceedings of the 2004 IEEE international conference on acoustics, speech, and signal processing (ICASSP 2004). Montreal, Quebec, Canada

  • Callison-Burch C, Osborne M, Koehn P (2006) Re-evaluation the role of bleu in machine translation research. In: Proceedings of the 11th conference of the European chapter of the association for computational linguistics: EACL 2006. Trento, Italy, pp 249–256

  • Callison-Burch C, Fordyce C, Koehn P, Monz C, Schroeder J (2007) (Meta-) evaluation of machine translation. In: StatMT ’07: Proceedings of the second workshop on statistical machine translation. Association for Computational Linguistics, Morristown, NJ, USA, pp 136–158

  • Efron B, Tibshirani R (1993) An introduction to the bootstrap. Chapman & Hall, Boca Raton

    MATH  Google Scholar 

  • Koehn P (2004) Statistical significance tests for machine translation evaluation. In: Proceedings of EMNLP 2004. Barcelona, Spain

  • Leusch G, Ueffing N, Ney H (2003) A novel string-to-string distance measurewith applications to machine translation evaluation. In: Proceedings of MT Summit IX. New Orleans, LA

  • Lin C-Y, Och FJ (2004) ORANGE: a method for evaluating automatic evaluation metrics for machine translation. In: COLING ’04: Proceedings of the 20th international conference on computational linguistics. Association for Computational Linguistics, Morristown, NJ, USA, p 501

  • Liu D, Gildea D (2005) Syntactic features for evaluation of machine translation. In: ACL 2005 workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization

  • Nießen S, Vogel S, Ney H, Tillmann C (1998) A DP based search algorithm for statistical machine translation. In: Proceedings of the 17th international conference on computational linguistics. Association for Computational Linguistics, Morristown, NJ, USA, pp 960–967

  • NIST (2003) Automatic evaluation of machine translation quality using N-gram co-occurrence statistics. Technical report, NIST, http://www.nist.gov/speech/tests/mt/doc/ngram-study.pdf

  • Owczarzak K, Genabith J, Way A (2007) Evaluating machine translation with LFG dependencies. Mach Transl 21(2): 95–119

    Article  Google Scholar 

  • Pado S, Galley M, Jurafsky D, Manning CD (2009) Robust machine translation evaluation with entailment features. In: Proceedings of the joint conference of the 47th annual meeting of the ACL and the 4th international joint conference on natural language processing of the AFNLP. Association for Computational Linguistics, Suntec, Singapore, pp 297–305

  • Papineni K, Roukos S, Ward T, Zhu W (2001) Bleu: a method for automatic evaluation of machine translation. Technical Report RC22176(W0109-022), IBM Research Division, Thomas J. Watson Research Center

  • Snover M, Dorr B, Schwartz R, Micciulla L, Makhoul J (2006) A study of translation edit rate with targeted human annotation. In: Proceedings AMTA, pp 223–231

  • Zhang Y (2008) Structured language model for statistical machine translation. Ph.D. thesis, Carnegie Mellon University, Pittsburgh, PA

  • Zhang Y, Vogel S, Waibel A (2004) Interpreting Bleu/NIST scores: how much improvement do we need to have a better system? In: Proceedings of the 4th international conference on language resources and evaluation. Lisbon, Portugal

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ying Zhang.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhang, Y., Vogel, S. Significance tests of automatic machine translation evaluation metrics. Machine Translation 24, 51–65 (2010). https://doi.org/10.1007/s10590-010-9073-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10590-010-9073-6

Keywords

Navigation