Summary of the paper

Title On the Origin of Errors: a Fine-Grained Analysis of MT and PE Errors and their Relationship
Authors Joke Daems, Lieve Macken and Sonia Vandepitte
Abstract In order to improve the symbiosis between machine translation (MT) system and post-editor, it is not enough to know that the output of one system is better than the output of another system. A fine-grained error analysis is needed to provide information on the type and location of errors occurring in MT and the corresponding errors occurring after post-editing (PE). This article reports on a fine-grained translation quality assessment approach which was applied to machine translated-texts and the post-edited versions of these texts, made by student post-editors. By linking each error to the corresponding source text-passage, it is possible to identify passages that were problematic in MT, but not after PE, or passages that were problematic even after PE. This method provides rich data on the origin and impact of errors, which can be used to improve post-editor training as well as machine translation systems. We present the results of a pilot experiment on the post-editing of newspaper articles and highlight the advantages of our approach.
Topics Evaluation Methodologies, Multilinguality
Full paper On the Origin of Errors: a Fine-Grained Analysis of MT and PE Errors and their Relationship
Bibtex @InProceedings{DAEMS14.532,
  author = {Joke Daems and Lieve Macken and Sonia Vandepitte},
  title = {On the Origin of Errors: a Fine-Grained Analysis of MT and PE Errors and their Relationship},
  booktitle = {Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)},
  year = {2014},
  month = {may},
  date = {26-31},
  address = {Reykjavik, Iceland},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Hrafn Loftsson and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {978-2-9517408-8-4},
  language = {english}
 }
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