著者

Seiya Kawano Koichiro Yoshino Satoshi Nakamura

出版者

The Japanese Society for Artificial Intelligence

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.36, no.4, pp.E-KC9_1-14, 2021-07-01 (Released:2021-07-01)

参考文献数

48

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Building a controllable neural conversation model (NCM) is an important task. In this paper, we focus on controlling the responses of NCMs using dialogue act labels of responses as conditions. We introduce a reinforcement learning framework involving adversarial learning for conditional response generation. Our proposed method has a new label-aware objective that encourages the generation of discriminative responses by the given dialogue act label while maintaining the naturalness of the generated responses. We compared the proposed method with conventional methods that generate conditional responses. The experimental results showed that our proposed method has higher controllability conditioned by the dialogue acts even though it has higher or comparable naturalness to the conventional models.

著者

河野 誠哉 Seiya Kawano

出版者

山梨学院大学経営情報学研究会

雑誌

山梨学院大学経営情報学論集 = JOURNAL OF MANAGEMENT INFORMATION SCIENCE (ISSN:13410806)

巻号頁・発行日

vol.21, pp.57-76, 2015-02-04

著者

河野 誠哉 カワノ セイヤ Seiya Kawano

雑誌

大学改革と生涯学習 : 山梨学院生涯学習センター紀要

巻号頁・発行日

vol.第17号, pp.29-44, 2013-03-27