(Institute of Electrical and Electronics Engineers (IEEE), 2013) N/A; N/A; N/A; Department of Computer Engineering; Department of Computer Engineering; Bozkurt, Elif; Asta, Shahriar; Özkul, Serkan; Yemez, Yücel; Erzin, Engin; PhD Student; PhD Student; Master Student; Faculty Member; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; N/A; N/A; 107907; 34503
Gesticulation is an essential component of face-to-face communication, and it contributes significantly to the natural and affective perception of human-to-human communication. In this work we investigate a new multimodal analysis framework to model relationships between intonational and gesture phrases using the hidden semi-Markov models (HSMMs). The HSMM framework effectively associates longer duration gesture phrases to shorter duration prosody clusters, while maintaining realistic gesture phrase duration statistics. We evaluate the multimodal analysis framework by generating speech prosody driven gesture animation, and employing both subjective and objective metrics.
