A Template Based Approach for Training NMT for Low-Resource Uralic Languages - A Pilot with Finnish-Reference-Cited by-同舟云学术

A Template Based Approach for Training NMT for Low-Resource Uralic Languages - A Pilot with Finnish

Published:2019-12-20 Issue: Volume: Page:
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Container-title:Proceedings of the 2019 2nd International Conference on Algorithms, Computing and Artificial Intelligence
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Author:

Hämäläinen Mika¹,Alnajjar Khalid²

Affiliation:

1. Department of Digital Humanities, University of Helsinki, Finland

2. Department of Computer Science, University of Helsinki, Finland

Publisher

ACM

Reference26 articles.

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3. Alina Karakanta Jon Dehdari and Josef van Genabith. 2018. Neural machine translation for low-resource languages without parallel corpora. Machine Translation 32 1 (01 Jun 2018) 167--189. https://doi.org/10.1007/s10590-017-9203-5 Alina Karakanta Jon Dehdari and Josef van Genabith. 2018. Neural machine translation for low-resource languages without parallel corpora. Machine Translation 32 1 (01 Jun 2018) 167--189. https://doi.org/10.1007/s10590-017-9203-5

4. Toan Q. Nguyen and David Chiang. 2017. Transfer Learning across Low-Resource Related Languages for Neural Machine Translation. CoRRabs/1708.09803 (2017). arXiv:1708.09803 http://arxiv.org/abs/1708.09803 Toan Q. Nguyen and David Chiang. 2017. Transfer Learning across Low-Resource Related Languages for Neural Machine Translation. CoRRabs/1708.09803 (2017). arXiv:1708.09803 http://arxiv.org/abs/1708.09803

5. Translating Low-Resource Languages by Vocabulary Adaptation from Close Counterparts

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