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    <abstract>Developing conversational systems that can converse in many languages is an interesting challenge for natural language processing. In this paper, we introduce multilingual addressee and response selection. In this task, a conversational system predicts an appropriate addressee and response for an input message in multiple languages. A key to developing such multilingual responding systems is how to utilize high-resource language data to compensate for low-resource language data. We present several knowledge transfer methods for conversational systems. To evaluate our methods, we create a new multilingual conversation dataset. Experiments on the dataset demonstrate the effectiveness of our methods.</abstract>
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%0 Conference Proceedings
%T Addressee and Response Selection for Multilingual Conversation
%A Sato, Motoki
%A Ouchi, Hiroki
%A Tsuboi, Yuta
%Y Bender, Emily M.
%Y Derczynski, Leon
%Y Isabelle, Pierre
%S Proceedings of the 27th International Conference on Computational Linguistics
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico, USA
%F sato-etal-2018-addressee
%X Developing conversational systems that can converse in many languages is an interesting challenge for natural language processing. In this paper, we introduce multilingual addressee and response selection. In this task, a conversational system predicts an appropriate addressee and response for an input message in multiple languages. A key to developing such multilingual responding systems is how to utilize high-resource language data to compensate for low-resource language data. We present several knowledge transfer methods for conversational systems. To evaluate our methods, we create a new multilingual conversation dataset. Experiments on the dataset demonstrate the effectiveness of our methods.
%U https://aclanthology.org/C18-1308
%P 3631-3644

Markdown (Informal)

[Addressee and Response Selection for Multilingual Conversation](https://aclanthology.org/C18-1308) (Sato et al., COLING 2018)

• Addressee and Response Selection for Multilingual Conversation (Sato et al., COLING 2018)

ACL

• Motoki Sato, Hiroki Ouchi, and Yuta Tsuboi. 2018. Addressee and Response Selection for Multilingual Conversation. In Proceedings of the 27th International Conference on Computational Linguistics, pages 3631–3644, Santa Fe, New Mexico, USA. Association for Computational Linguistics.