Abstract
This paper presents work on the manual and automatic evaluation of the online available machine translation (MT) service Google Translate, for the English-Croatian language pair in legislation and general domains. The experimental study is conducted on the test set of 200 sentences in total. Human evaluation is performed by native speakers, using the criteria of fluency and adequacy, and it is enriched by error analysis. Automatic evaluation is performed on a single reference set by using the following metrics: BLEU, NIST, F-measure and WER. The influence of lowercasing, tokenization and punctuation is discussed. Pearson’s correlation between automatic metrics is given, as well as correlation between the two criteria, fluency and adequacy, and automatic metrics.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Callison-Burch, C., Fordyce, C., Koehn, P., Monz, C., Schroeder, J.: Meta-evaluation of machine translation. In: Proceedings of the Second Workshop on Statistical Machine Translation, pp. 136–158 (2007)
Coughlin, D.: Correlating automated and human assessments of machine translation quality. In: Proceedings of MT Summit IX, pp. 63–70 (2003)
Doddington, G.: Automatic evaluation of machine translation quality using n-gram co-occurrence statistics. In: Proceedings of the Second International Conference on Human Language Technology Research, pp. 138–145. Morgan Kaufmann Publishers Inc. (2002)
Farrús Cabeceran, M., Ruiz Costa-Jussà, M., Mariño Acebal, J.B., Rodríguez Fonollosa, J.A., et al.: Linguistic-based evaluation criteria to identify statistical machine translation errors. In: Proceedings of EAMT, pp. 52–57 (2010)
Flanagan, M.: Error classification for mt evaluation. In: Technology Partnerships for Crossing the Language Barrier: Proceedings of the First Conference of the Association for Machine Translation in the Americas, pp. 65–72 (1994)
Hovy, E., King, M., Popescu-Belis, A.: Principles of context-based machine translation evaluation. Machine Translation 17(1), 43–75 (2002)
Koehn, P.: Statistical significance tests for machine translation evaluation. In: Proceedings of EMNLP, vol. 4, pp. 388–395 (2004)
Koehn, P.: Statistical Machine Translation, vol. 11. Cambridge University Press (2010)
Leusch, G., Ueffing, N., Ney, H., et al.: A novel string-to-string distance measure with applications to machine translation evaluation. In: Proceedings of MT Summit IX, pp. 33–40 (2003)
Melamed, I.D., Green, R., Turian, J.P.: Precision and recall of machine translation. In: Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Companion Volume of the Proceedings of HLT-NAACL 2003–Short Papers, vol. 2, pp. 61–63. Association for Computational Linguistics (2003)
Papineni, K., Roukos, S., Ward, T., Zhu, W.J.: Bleu: a method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, pp. 311–318. Association for Computational Linguistics (2002)
Stymne, S.: Blast: A tool for error analysis of machine translation output. In: Proc. of the 49th ACL, HLT, Systems Demonstrations, pp. 56–61 (2011)
Tillmann, C., Vogel, S., Ney, H., Zubiaga, A., Sawaf, H.: Accelerated dp based search for statistical translation. In: European Conf. on Speech Communication and Technology, pp. 2667–2670 (1997)
Vilar, D., Xu, J., d’Haro, L.F., Ney, H.: Error analysis of statistical machine translation output. In: Proceedings of LREC, pp. 697–702 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Brkić, M., Seljan, S., Vičić, T. (2013). Automatic and Human Evaluation on English-Croatian Legislative Test Set. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2013. Lecture Notes in Computer Science, vol 7817. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37256-8_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-37256-8_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37255-1
Online ISBN: 978-3-642-37256-8
eBook Packages: Computer ScienceComputer Science (R0)