A frequency-domain analysis of head-motion prediction
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Mood swings: expressive speech animation
ACM Transactions on Graphics (TOG)
Natural head motion synthesis driven by acoustic prosodic features: Virtual Humans and Social Agents
Computer Animation and Virtual Worlds - CASA 2005
Effects of head movement on perceptions of humanoid robot behavior
Proceedings of the 1st ACM SIGCHI/SIGART conference on Human-robot interaction
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Computers in Entertainment (CIE) - SPECIAL ISSUE: Media Arts and Games (Part II)
Designing effective gaze mechanisms for virtual agents
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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Lifelike interface agents (e.g. talking avatars) have been increasingly used in human-computer interaction applications. In this work, we quantitatively analyze how human perception is affected by audio-head motion characteristics of talking avatars. Specifically, we quantify the correlation between perceptual user ratings (obtained via user study) and joint audio-head motion features as well as head motion patterns in the frequency-domain. Our quantitative analysis results clearly show that the correlation coefficient between the pitch of speech signals (but not the RMS energy of speech signals) and head motions is approximately linearly proportional to the perceptual user rating, and a larger proportion of high frequency signals in talking avatar head movements tends to degrade the user perception in terms of naturalness.