[2O5-OS-2a] 人間と共生する対話知能

[2O5-OS-2a-03] Prediction of Validating Response from Emotional Storytelling Corpus

〇Zi Haur Pang¹, Yahui Fu¹, Divesh Lala¹, Keiko Ochi¹, Koji Inoue¹, Tatsuya Kawahara¹ (1. Kyoto University)

Keywords:Validation, Empathy, Affective Computing, Spoken Dialogue System, Natural Language Understanding

Empathy is the capacity to place oneself in another person's position. To show empathy in conversation, validation is one of the methods that can be used. Validation is a technique to show understanding of what has happened and how they feel. This study aims to develop a model that determines the necessity of generating validating responses in conversation through its prior utterance. TUT emotional storytelling corpus (TESC) has been used in this study. The prior utterances have been analyzed for various aspects, and the results indicate that emotional phrases, laughing, emphasizing phrases, and particle types in the last word affect the generation of validating responses and thus serve as the basis for developing the model in this study. Using a logistic regression model, we can predict the validating responses with an accuracy of 62.7%, and a recall of 60.0%.