상세정보
학술대회
Identifying Principal Social Signals in Private Student-Teacher Interactions for Robot-Enhanced Education
- 발행일
- 201308
- 출처
- International Symposium on Robot and Human Interactive Communication (RO-MAN) 2013, pp.621-626
- 협약과제
- 12VC2100, 인간 친화적 로봇 서비스 환경에서 판단 적합성 90%이상인 복합지식 기반 판단 및 의미기반 로봇 표현 기술 개발, 김재홍
- 초록
- Providing robots with social intelligence is critical for making entertaining and sustainable human-robot interactions. The first step to get good social intelligence is to appropriately understand the meaning of social signals emitted by interactors. In this paper, we introduce a preliminary study on identifying principal social signals in interpreting participant's engagement and confirmation intention in 1:1 interactions. We annotated 6 video recordings of private teacher-student interactions with 20 social signals and their interpretations, and built pattern data sets with different subsets of social signals. C4.5 based decision trees were generated using the pattern data sets and the recall rates were compared. Also attribute selection was performed to find principal social signals. The results showed that verbal signal was the most principal for determining engagement, and the combination of gaze and verbal signal for confirmation intention. © 2013 IEEE.
- KSP 제안 키워드
- Attribute selection, Data sets, Decision Tree(DT), Human-Robot Interaction(HRI), Preliminary study, Social Intelligence, Social Signals, Student-teacher, Video recording