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Title:

A Teacher-Student Framework for Zero-Resource Neural Machine Translation

Abstract:

While end-to-end neural machine translation (NMT) has made remarkable progress recently, it still suffers from the data scarcity problem for low-resource language pairs and domains. In this paper, we propose a method for zero-resource NMT by assuming that parallel sentence shave close probabilities of generating a sentence in a third language. Based on this assumption, our method is able to train a source-to-target NMT model (“student”) without parallel corpora available, guided by an existing pivot-to-target NMT model (“teacher”) on a source-pivot parallel corpus. Experimental results show that the proposed method significantly improves over a baseline pivot-based model by +3.0 BLEU points across various language pairs.

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# Title Author Topic Medium Score
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10 403 Forbidden None
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26 ACL 2018 Highlights: Understanding Representations and Evaluation in More Challenging Settings Sebastian Ruder 9999
27 A Correlational Encoder Decoder Architecture for Pivot Based Sequence Generation Amrita Saha, Mitesh M Khapra, Sarath Chandar, Janarthanan Rajendran... 9999
28 Pointing the Unknown Words Caglar Gulcehre, Sungjin Ahn, Ramesh Nallapati, Bowen Zhou, Yoshua ... 9999
29 RL in NMT: The Good, the Bad and the Ugly Julia Kreutzer 1336
30 RL in NMT: The Good, the Bad and the Ugly Julia Kreutzer 1336
31 Transfer Learning for Low-Resource Neural Machine Translation Barret Zoph, Deniz Yuret, Jonathan May, Kevin Knight 9999
32 Improving Neural Text Simplification Model with Simplified Corpora Jipeng Qiang 1198
33 Addressing the rare word problem in neural machine translation Minh-Thang Luong, Ilya Sutskever, Quoc V Le, Oriol Vinyals, Wojciec... 9999
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35 Pointing the Unknown Words Caglar Gulcehre, Sungjin Ahn, Ramesh Nallapati, Bowen Zhou, Yoshua ... 9999
36 Achieving open vocabulary neural machine translation with hybrid word-character models Minh-Thang Luong, Christopher D Manning 9999
37 ACL 2018 Highlights: Understanding Representations and Evaluation in More Challenging Settings Sebastian Ruder 9999
38 Statistical Machine Translation Philipp Koehn 1143
39 Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism Orhan Firat, Kyunghyun Cho, Yoshua Bengio 9999
40 Context-Dependent Word Representation for Neural Machine Translation Heeyoul Choi, Kyunghyun Cho, Yoshua Bengio 9999
41 Embedding word similarity with neural machine translation Felix Hill, Kyunghyun Cho, Sebastien Jean, Coline Devin, Yoshua Bengio 9999
42 Neural Machine Translation: Basics, Practical Aspects and Recent Trends Fabien Cromieres, Toshiaki Nakazawa, Raj Dabre 1197
43 Deep Learning for NLP, advancements and trends in 2017 Javier 1181
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45 Learning to Represent Words in Context with Multilingual Supervision Kazuya Kawakami, Chris Dyer 9999
46 Adversarial Neural Machine Translation Lijun Wu, Yingce Xia, Li Zhao, Fei Tian, Tao Qin, Jianhuang Lai, Ti... 9999
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48 Multilingual distributed representations without word alignment Karl Moritz Hermann, Phil Blunsom 9999
49 Neural versus Phrase-Based Machine Translation Quality: a Case Study Luisa Bentivogli, Arianna Bisazza, Mauro Cettolo, Marcello Federico 9999
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