BLEU: a Method for Automatic Evaluation of Machine Translation

Papineni et al., 2002, BLEU (Proceedings of the 40th Annual Meeting of ACL)

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6 Conclusion

  1. How does BLEU achieve its high correlation with human judgments, in its authors’ words?
    By averaging out individual sentence judgment errors over a test corpus rather than trying to divine the exact human judgment for every sentence: “quantity leads to quality”.
    • Papineni et al., 2002, BLEU (Proceedings of the 40th Annual Meeting of ACL), §6
  2. Beyond MT, where did the authors think BLEU could apply?
    Summarization and similar natural language generation tasks, since MT and summarization can both be viewed as generation from a textual context.
    • Papineni et al., 2002, BLEU (Proceedings of the 40th Annual Meeting of ACL), §6

Source

  • Kishore Papineni, Salim Roukos, Todd Ward and Wei-Jing Zhu. 2002. BLEU: a Method for Automatic Evaluation of Machine Translation. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, pp. 311–318. https://aclanthology.org/P02-1040/