JSAI2020

Presentation information

Interactive Session

[3Rin4] Interactive 1

Thu. Jun 11, 2020 1:40 PM - 3:20 PM Room R01 (jsai2020online-2-33)

[3Rin4-94] A conditional response generation model with intention reconstruction as a constraint

Hidekazu Takatsuji1,2, 〇Koichiro Yoshino1,2, Katsuhito Sudoh1,2, Satoshi Nakamura1,2 (1. NARA Institute of Science and Technology, 2. RIKEN Center for Advanced Intelligence Project (AIP))

Keywords:conditional language generation, dialogue system

Language generation is a task to generate sentences corresponding to a given intention. Existing researches of neural language generation models gave the intention to encoder; however, there was no strong constraint to contain the intention in generation results. In this research, we propose a learning method for the language generation system to ensure the generated sentence contains the given intention. We evaluated the effect of the proposed method in both automatic and human subjective evaluation.

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