Modeling Japanese Praising Behavior by Analyzing Audio and Visual Behaviors

Praising behavior is considered to be verbal and nonverbal behaviors that expresses praise the behavior and character of the target. However, how one should use verbal and nonverbal behaviors to successfully praise a target has not been clarified. Therefore, we focus on attempts to analyze praising behavior in Japanese dialogue using verbal and nonverbal behaviors. In this study, we attempted to analyze the relationship between praising skills and human behaviors in Japanese dialogue by focusing on voice, head, and face behaviors. First, we created a new dialogue corpus in Japanese containing voice, head, and face behaviors from individuals giving praise (praiser) and receiving praise (receiver), as well as the degree of success of praising (praising score). Second, we developed machine learning models that uses features related to voice, head, and face behaviors to estimate praising skills to clarify which features of the praiser and receiver are important for estimating praising skills. Evaluation resulte showed that some audio features of the praiser are particularly important for estimation of praising skills. Our analysis results demonstrated the importance of features related to the zero-crossing rate, MFCCs of the praiser. Analyzing the features of high importance revealed that the praiser should praise with specific words that mean amazing or great in Japanese and the voice quality of the praiser is considered to be important for praising successfully.