Analyzing Nonverbal Behaviors along with Praising

Abstract

In this work, as a first attempt to analyze the relationship between praising skills and human behavior in dialogue, we focus on head and face behavior. We create a new dialogue corpus including face and head behavior information of persons who give praise (praiser) and receive praise (receiver) and the degree of success of praising (praising score). We also create a machine learning model that uses features related to head and face behavior to estimate praising score, clarify which features of the praiser and receiver are important in estimating praising score. The analysis results showed that features of the praiser and receiver are important in estimating praising score and that features related to utterance, head, gaze, and chin were important. The analysis of the features of high importance revealed that the praiser and receiver should face each other without turning their heads to the left or right, and the longer the praiser's utterance, the more successful the praising.