2025 Volume 33 Pages 31-39
Opportunities to remotely communicate have been increasing since the start of the COVID-19 pandemic. Praising behavior is considered an important element of daily life and social activities. However, many people are uncertain about the best way to praise a partner. Such individuals may have difficulty understanding how to behave in order to improve their own praising skills. To solve this problem, we aim to develop a system that automatically evaluates whether a person is praising the other person in a remote dialogue, and reviews the utterances in which the person is praising a partner. As a first step toward achieving this goal, we attempted to detect praising behaviors from speaker's multimodal information in remote dialogues. Specifically, we constructed machine learning models for detecting praising behaviors using a dialogue corpus that contains remote dialogue data and the results of judgments about praising behaviors. As a result, we clarified that the praising behaviors are detectable based on multimodal information in remote dialogues. Furthermore, we clarified that the highest detection performance was achieved with the praiser's linguistic information and the receiver's linguistic information.
