Zero-resource translation with multi-lingual neural machine translation

Orhan Firat; Baskaran Sankaran; Yaser Al-Onaizan; Fatos T. Yarman Vural; Kyunghyun Cho

Zero-resource translation with multi-lingual neural machine translation

Orhan Firat, Baskaran Sankaran, Yaser Al-Onaizan, Fatos T. Yarman Vural, Kyunghyun Cho

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, we propose a novel finetuning algorithm for the recently introduced multi-way, multilingual neural machine translate that enables zero-resource machine translation. When used together with novel many-to-one translation strategies, we empirically show that this finetuning algorithm allows the multi-way, multilingual model to translate a zero-resource language pair (1) as well as a single-pair neural translation model trained with up to 1M direct parallel sentences of the same language pair and (2) better than pivot-based translation strategy, while keeping only one additional copy of attention-related parameters.

Original language	English (US)
Title of host publication	EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings
Publisher	Association for Computational Linguistics (ACL)
Pages	268-277
Number of pages	10
ISBN (Electronic)	9781945626258
State	Published - Jan 1 2016
Event	2016 Conference on Empirical Methods in Natural Language Processing, EMNLP 2016 - Austin, United States Duration: Nov 1 2016 → Nov 5 2016

Publication series

Name	EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings

Conference

Conference	2016 Conference on Empirical Methods in Natural Language Processing, EMNLP 2016
Country/Territory	United States
City	Austin
Period	11/1/16 → 11/5/16

ASJC Scopus subject areas

Computer Science Applications
Information Systems
Computational Theory and Mathematics

Cite this

Firat, O., Sankaran, B., Al-Onaizan, Y., Yarman Vural, F. T., & Cho, K. (2016). Zero-resource translation with multi-lingual neural machine translation. In EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings (pp. 268-277). (EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings). Association for Computational Linguistics (ACL).

Zero-resource translation with multi-lingual neural machine translation. / Firat, Orhan; Sankaran, Baskaran; Al-Onaizan, Yaser et al.
EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings. Association for Computational Linguistics (ACL), 2016. p. 268-277 (EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Firat, O, Sankaran, B, Al-Onaizan, Y, Yarman Vural, FT & Cho, K 2016, Zero-resource translation with multi-lingual neural machine translation. in EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings. EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings, Association for Computational Linguistics (ACL), pp. 268-277, 2016 Conference on Empirical Methods in Natural Language Processing, EMNLP 2016, Austin, United States, 11/1/16.

Firat O, Sankaran B, Al-Onaizan Y, Yarman Vural FT, Cho K. Zero-resource translation with multi-lingual neural machine translation. In EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings. Association for Computational Linguistics (ACL). 2016. p. 268-277. (EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings).

Firat, Orhan ; Sankaran, Baskaran ; Al-Onaizan, Yaser et al. / Zero-resource translation with multi-lingual neural machine translation. EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings. Association for Computational Linguistics (ACL), 2016. pp. 268-277 (EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings).

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Zero-resource translation with multi-lingual neural machine translation

Abstract

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ASJC Scopus subject areas

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