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Enhancing Pivot Translation Using Grammatical and Morphological Information

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Computational Linguistics (PACLING 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 781))

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Abstract

Pivot translation can be one of the solutions to overcome the problem of unavailable large bilingual corpora for training statistical machine translation models. Nevertheless, the conventional pivot method, which connect source to target phrases via common pivot phrases, lacks some potential connections when pivoting via the surface form of pivot phrases. In this work, we improve the pivot translation method by integrating grammatical and morphological information to connect pivot phrases instead of using only the surface form. Experiments were conducted on several Southeast Asian low-resource language pairs: Indonesian-Vietnamese, Malay-Vietnamese, and Filipino-Vietnamese. By integrating grammatical and morphological information, the proposed method achieved a significant improvement of 0.5 BLEU points. This showed the effectiveness of integrating grammatical and morphological features to pivot translation.

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Notes

  1. 1.

    https://github.com/nguyenlab/pivot-linguistics.

  2. 2.

    https://wit3.fbk.eu/.

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Authors and Affiliations

  1. School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, Japan

    Hai-Long Trieu & Le-Minh Nguyen

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  1. Hai-Long Trieu
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  2. Le-Minh Nguyen
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Correspondence to Hai-Long Trieu .

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Editors and Affiliations

  1. Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan

    Kôiti Hasida

  2. Natural Language Processing Lab, University of Computer Studies, Yangon, Yangon, Myanmar

    Win Pa Pa

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Trieu, HL., Nguyen, LM. (2018). Enhancing Pivot Translation Using Grammatical and Morphological Information. In: Hasida, K., Pa, W. (eds) Computational Linguistics. PACLING 2017. Communications in Computer and Information Science, vol 781. Springer, Singapore. https://doi.org/10.1007/978-981-10-8438-6_12

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  • DOI: https://doi.org/10.1007/978-981-10-8438-6_12

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  • Online ISBN: 978-981-10-8438-6

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