Multi-way, multilingual neural machine translation

Date

2017-09-01

Author

Firat, Orhan
Cho, Kyunghyun
Sankaran, Baskaran
Yarman Vural, Fatoş Tunay
Bengio, Yoshua

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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We propose multi-way, multilingual neural machine translation. The proposed approach enables a single neural translation model to translate between multiple languages, with a number of parameters that grows only linearly with the number of languages. This is made possible by having a single attention mechanism that is shared across all language pairs. We train the proposed multi-way, multilingual model on ten language pairs from WMT'15 simultaneously and observe clear performance improvements over models trained on only one language pair. We empirically evaluate the proposed model on low-resource language translation tasks. In particular, we observe that the proposed multilingual model outperforms strong conventional statistical machine translation systems on Turkish-English and Uzbek-English by incorporating the resources of other language pairs. (C) 2016 Elsevier Ltd. All rights reserved

Subject Keywords

Low resource translation, Multi-lingual, Neural machine translation

URI

https://hdl.handle.net/11511/42997

Journal

COMPUTER SPEECH AND LANGUAGE

DOI

https://doi.org/10.1016/j.csl.2016.10.006

Collections

Department of Computer Engineering, Article

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Citation Formats

O. Firat, K. Cho, B. Sankaran, F. T. Yarman Vural, and Y. Bengio, “Multi-way, multilingual neural machine translation,” COMPUTER SPEECH AND LANGUAGE, pp. 236–252, 2017, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/42997.