Detecting Politeness and frustration state of a child in a conversational computer game

In this study, we investigate politeness and frustration behavior of children during their spoken interaction with computer characters in a game. We focus on automatically detecting frustrated, polite and neutral attitudes from the child’s speech (acoustic and language) communication cues and study their differences as a function of age and gender. The study is based on a Wizard-of-Oz dialog corpus of 103 children playing a voice activated computer game. Statistical analysis revealed that there was a significant gender effect on politeness with girls in this data exhibiting more explicit politeness markers. The analysis also showed that there is a positive correlation between frustration and the number of dialog turns reflecting the fact that longer time spent solving the puzzle of the game led to a more frustrated child. By combining acoustic and language cues for the task of automatic detection of politeness and frustration, we obtain average accuracy of 84.7% and 71.3%, respectively, by using age dependent models and 85% and 72%, respectively, for gender dependent models.