Improving Low-Resource NMT with Parser Generated Syntactic Phrases

Author:

Gupta Kamal Kumar,Sen Sukanta,Ekbal Asif,Bhattacharyya Pushpak

Publisher

Springer Nature Switzerland

Reference23 articles.

1. Bahdanau, D., Cho, K., Bengio, Y.: Neural machine translation by jointly learning to align and translate. In: International Conference on Learning Representation (ICLR) (2015)

2. Banerjee, S., Lavie, A.: METEOR: an automatic metric for MT evaluation with improved correlation with human judgments. In: Proceedings of the ACL Workshop on Intrinsic and Extrinsic Evaluation Measures for Machine Translation and/or Summarization, pp. 65–72. Association for Computational Linguistics (2005). http://www.aclweb.org/anthology/W05-0909

3. Bojar, O., et al.: Findings of the 2014 workshop on statistical machine translation. In: Proceedings of the Ninth Workshop on Statistical Machine Translation, pp. 12–58 (2014)

4. Bojar, O., et al.: Findings of the 2016 conference on machine translation. In: ACL 2016 First Conference on Machine Translation (WMT16), pp. 131–198. The Association for Computational Linguistics (2016)

5. Bojar, O., et al.: Hindencorp-Hindi-English and Hindi-only corpus for machine translation. In: LREC, pp. 3550–3555 (2014)

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