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CCMT 2019 Machine Translation Evaluation Report

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Machine Translation (CCMT 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1104))

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Abstract

This paper introduces the evaluation procedure, evaluation data, participants and evaluation results of 2019 (15th) China Conference on Machine Translation (CCMT 2019) evaluation campaign. Compared with the last evaluation campaign (CWMT 2018), CCMT 2019 MT evaluation is characterized as follows: a new speech translation task is fulfilled; the translation quality estimation task is augmented with a word level track in addition to the sentence level track. Meanwhile, CCMT 2019 receives increases in the number of participants and systems submitted. This paper presents the anonymous evaluation results of all tasks, with a brief summarization of the techniques applied in this evaluation campaign.

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Notes

  1. 1.

    https://ccmt2019.jxnu.edu.cn/page/main1923/CCMT2019_Evaluation_report.zip (in Chinese).

  2. 2.

    One team can’t be contacted after registration, which is not counted as in the 30 teams.

  3. 3.

    http://www.cs.umd.edu/~snover/tercom/.

  4. 4.

    Available only in Chinese via https://ccmt2019.jxnu.edu.cn/page/main1923/CCMT2019_Evaluation_report.zip.

  5. 5.

    https://github.com/fxsjy/jieba.

  6. 6.

    https://github.com/moses-smt/mosesdecoder/blob/master/scripts/tokenizer/tokenizer.perl.

  7. 7.

    https://github.com/tensorflow/tensor2tensor/blob/master/tensor2tensor/data_generators/text_encoder_build_subword.py.

  8. 8.

    https://github.com/paddlepaddle/paddle.

  9. 9.

    http://thulac.thunlp.org/.

  10. 10.

    https://nlp.stanford.edu/software/segmenter.shtml.

References

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Acknowledgments

Our special gratitude goes to partners who providing the data resources (with no special order): Alibaba (China) Co., Ltd., Baidu inc., Beijing Lingosail Tech Co., Ltd., DianTongShuJu Co., Ltd., Northeastern University, Harbin Institute of Technology, Nanjing University, Inner Mongolia University, Qinghai Normal University, Northwest Minzu University, Tibet University, Xiamen University, Institute of Intelligent Machines. CAS, Institute of Computing Technology (CAS), The Xinjiang Technical Institute of Physics & Chemistry (CAS), and Institute of Automation (CAS). We would also express gratitude to the Technical Committee of Machine Translation of CIPSC and all the participating teams for their various supports and contributions to CCMT 2019 evaluation campaign.

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Correspondence to Muyun Yang .

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Yang, M. et al. (2019). CCMT 2019 Machine Translation Evaluation Report. In: Huang, S., Knight, K. (eds) Machine Translation. CCMT 2019. Communications in Computer and Information Science, vol 1104. Springer, Singapore. https://doi.org/10.1007/978-981-15-1721-1_11

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  • DOI: https://doi.org/10.1007/978-981-15-1721-1_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-1720-4

  • Online ISBN: 978-981-15-1721-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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