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        <title>Tokyo Metropolitan University Neural Machine Translation System for WAT 2017</title>
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        <namePart type="given">Yukio</namePart>
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        <namePart type="given">Mamoru</namePart>
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            <title>Proceedings of the 4th Workshop on Asian Translation (WAT2017)</title>
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        <name type="personal">
            <namePart type="given">Toshiaki</namePart>
            <namePart type="family">Nakazawa</namePart>
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            <namePart type="given">Isao</namePart>
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            <publisher>Asian Federation of Natural Language Processing</publisher>
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    <abstract>In this paper, we describe our neural machine translation (NMT) system, which is based on the attention-based NMT and uses long short-term memories (LSTM) as RNN. We implemented beam search and ensemble decoding in the NMT system. The system was tested on the 4th Workshop on Asian Translation (WAT 2017) shared tasks. In our experiments, we participated in the scientific paper subtasks and attempted Japanese-English, English-Japanese, and Japanese-Chinese translation tasks. The experimental results showed that implementation of beam search and ensemble decoding can effectively improve the translation quality.</abstract>
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%0 Conference Proceedings
%T Tokyo Metropolitan University Neural Machine Translation System for WAT 2017
%A Matsumura, Yukio
%A Komachi, Mamoru
%Y Nakazawa, Toshiaki
%Y Goto, Isao
%S Proceedings of the 4th Workshop on Asian Translation (WAT2017)
%D 2017
%8 November
%I Asian Federation of Natural Language Processing
%C Taipei, Taiwan
%F matsumura-komachi-2017-tokyo
%X In this paper, we describe our neural machine translation (NMT) system, which is based on the attention-based NMT and uses long short-term memories (LSTM) as RNN. We implemented beam search and ensemble decoding in the NMT system. The system was tested on the 4th Workshop on Asian Translation (WAT 2017) shared tasks. In our experiments, we participated in the scientific paper subtasks and attempted Japanese-English, English-Japanese, and Japanese-Chinese translation tasks. The experimental results showed that implementation of beam search and ensemble decoding can effectively improve the translation quality.
%U https://aclanthology.org/W17-5716
%P 160-166

Markdown (Informal)

[Tokyo Metropolitan University Neural Machine Translation System for WAT 2017](https://aclanthology.org/W17-5716) (Matsumura & Komachi, WAT 2017)

• Tokyo Metropolitan University Neural Machine Translation System for WAT 2017 (Matsumura & Komachi, WAT 2017)

ACL

• Yukio Matsumura and Mamoru Komachi. 2017. Tokyo Metropolitan University Neural Machine Translation System for WAT 2017. In Proceedings of the 4th Workshop on Asian Translation (WAT2017), pages 160–166, Taipei, Taiwan. Asian Federation of Natural Language Processing.