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ファイル | 記述 | サイズ | フォーマット | |
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j.csl.2022.101469.pdf | 985.73 kB | Adobe PDF | 見る/開く |
タイトル: | Character expression for spoken dialogue systems with semi-supervised learning using Variational Auto-Encoder |
著者: | Yamamoto, Kenta Inoue, Koji ![]() ![]() ![]() Kawahara, Tatsuya ![]() ![]() ![]() |
著者名の別形: | 山本, 賢太 井上, 昂治 河原, 達也 |
キーワード: | Spoken dialogue system Character Semi-supervised learning Variational auto-encoder (VAE) |
発行日: | Apr-2023 |
出版者: | Elsevier BV |
誌名: | Computer Speech & Language |
巻: | 79 |
論文番号: | 101469 |
抄録: | Character of spoken dialogue systems is important not only for giving a positive impression of the system but also for gaining rapport from users. We have proposed a character expression model for spoken dialogue systems. The model expresses three character traits (extroversion, emotional instability, and politeness) of spoken dialogue systems by controlling spoken dialogue behaviors: utterance amount, backchannel, filler, and switching pause length. One major problem in training this model is that it is costly and time-consuming to collect many pair data of character traits and behaviors. To address this problem, semi-supervised learning is proposed based on a variational auto-encoder that exploits both the limited amount of labeled pair data and unlabeled corpus data. It was confirmed that the proposed model can express given characters more accurately than a baseline model with only supervised learning. We also implemented the character expression model in a spoken dialogue system for an autonomous android robot, and then conducted a subjective experiment with 75 university students to confirm the effectiveness of the character expression for specific dialogue scenarios. The results showed that expressing a character in accordance with the dialogue task by the proposed model improves the user’s impression of the appropriateness in formal dialogue such as job interview. |
著作権等: | © 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. |
URI: | http://hdl.handle.net/2433/281689 |
DOI(出版社版): | 10.1016/j.csl.2022.101469 |
出現コレクション: | 学術雑誌掲載論文等 |

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