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        <title>Controlling Japanese Honorifics in English-to-Japanese Neural Machine Translation</title>
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    <name type="personal">
        <namePart type="given">Weston</namePart>
        <namePart type="family">Feely</namePart>
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        <namePart type="family">Hasler</namePart>
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    <name type="personal">
        <namePart type="given">Adrià</namePart>
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    <abstract>In the Japanese language different levels of honorific speech are used to convey respect, deference, humility, formality and social distance. In this paper, we present a method for controlling the level of formality of Japanese output in English-to-Japanese neural machine translation (NMT). By using heuristics to identify honorific verb forms, we classify Japanese sentences as being one of three levels of informal, polite, or formal speech in parallel text. The English source side is marked with a feature that identifies the level of honorific speech present in the Japanese target side. We use this parallel text to train an English-Japanese NMT model capable of producing Japanese translations in different honorific speech styles for the same English input sentence.</abstract>
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    <identifier type="doi">10.18653/v1/D19-5203</identifier>
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        <date>2019-nov</date>
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            <start>45</start>
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%0 Conference Proceedings
%T Controlling Japanese Honorifics in English-to-Japanese Neural Machine Translation
%A Feely, Weston
%A Hasler, Eva
%A de Gispert, Adrià
%S Proceedings of the 6th Workshop on Asian Translation
%D 2019
%8 nov
%I Association for Computational Linguistics
%C Hong Kong, China
%F feely-etal-2019-controlling
%X In the Japanese language different levels of honorific speech are used to convey respect, deference, humility, formality and social distance. In this paper, we present a method for controlling the level of formality of Japanese output in English-to-Japanese neural machine translation (NMT). By using heuristics to identify honorific verb forms, we classify Japanese sentences as being one of three levels of informal, polite, or formal speech in parallel text. The English source side is marked with a feature that identifies the level of honorific speech present in the Japanese target side. We use this parallel text to train an English-Japanese NMT model capable of producing Japanese translations in different honorific speech styles for the same English input sentence.
%R 10.18653/v1/D19-5203
%U https://aclanthology.org/D19-5203
%U https://doi.org/10.18653/v1/D19-5203
%P 45-53

Markdown (Informal)

[Controlling Japanese Honorifics in English-to-Japanese Neural Machine Translation](https://aclanthology.org/D19-5203) (Feely et al., EMNLP 2019)

• Controlling Japanese Honorifics in English-to-Japanese Neural Machine Translation (Feely et al., EMNLP 2019)

ACL

• Weston Feely, Eva Hasler, and Adrià de Gispert. 2019. Controlling Japanese Honorifics in English-to-Japanese Neural Machine Translation. In Proceedings of the 6th Workshop on Asian Translation, pages 45–53, Hong Kong, China. Association for Computational Linguistics.