Emotional Speech Corpus for Persuasive Dialogue System

Sara Asai, Koichiro Yoshino, Seitaro Shinagawa, Sakriani Sakti, Satoshi Nakamura


Abstract
Expressing emotion is known as an efficient way to persuade one’s dialogue partner to accept one’s claim or proposal. Emotional expression in speech can express the speaker’s emotion more directly than using only emotion expression in the text, which will lead to a more persuasive dialogue. In this paper, we built a speech dialogue corpus in a persuasive scenario that uses emotional expressions to build a persuasive dialogue system with emotional expressions. We extended an existing text dialogue corpus by adding variations of emotional responses to cover different combinations of broad dialogue context and a variety of emotional states by crowd-sourcing. Then, we recorded emotional speech consisting of of collected emotional expressions spoken by a voice actor. The experimental results indicate that the collected emotional expressions with their speeches have higher emotional expressiveness for expressing the system’s emotion to users.
Anthology ID:
2020.lrec-1.62
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
491–497
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.62
DOI:
Bibkey:
Cite (ACL):
Sara Asai, Koichiro Yoshino, Seitaro Shinagawa, Sakriani Sakti, and Satoshi Nakamura. 2020. Emotional Speech Corpus for Persuasive Dialogue System. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 491–497, Marseille, France. European Language Resources Association.
Cite (Informal):
Emotional Speech Corpus for Persuasive Dialogue System (Asai et al., LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.62.pdf