Data mining for automatic communication behaviors identification

Children's interpersonal communication, personality, social adaptive capability, and learning ability are affected by the interaction with their caregivers. Therefore, it is important to improve the communication ability of caregiver and it can also improve children's language ability and communication behavior. We have to find the communication behavior of child and his/her caregiver from interactive actions and used this information to provide useful information to improve their communication ability. However, the communication behavior should be manually identified and it is a time-consuming process. In this paper, we proposed a data mining algorithm to find the communication behavior. First, child and caregiver have to play three games and the interactive actions are also recorded in video and speech. Those video and speech can help clinical linguists to evaluate the performance of communication behavior. Second, those interactive actions are processed by speech recognition, speech act annotation, and interchange annotation. The speech act and interchange are the most important factors of communication behavior. Third, data mining is proposed to find the most frequent sequences of speech act and interchange. This is the basis information of user's communication behavior. Finally, clinical linguist can easily evaluate the performance of caregiver and provide suggestions to improve their communication ability. Experimental results reveal the usefulness of the proposed method and system.