Prosody-driven robot arm gestures generation in human-robot interaction

In multimodal human-robot interaction(HRI), the process of communication can be established through verbal, nonverbal, and/or para-verbal cues. The linguistic literature [3] shows that para-verbal and non-verbal communications are naturally synchronized. This research focuses on the relation between non-verbal and para-verbal communication by mapping prosody cues to the corresponding arm gestures. Our approach for synthesizing arm gestures uses the coupled hidden Markov models (CHMMs), which could be seen as a collection of HMMs modeling the segmented prosodic characteristics´ stream and the segmented rotation characteristics´ streams of the two arms´ articulations [4] [1]. Nao robot was used for tests.