Body Language Animation Synthesis from Prosody

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Abstract/Contents

Abstract: Human communication involves not only speech, but also a wide variety of gestures and body motions. Interactions in virtual environments often lack this multi-modal aspect of communication. This thesis presents a method for automatically synthesizing body language animations directly from the participants’ speech signals, without the need for additional input. The proposed system generates appropriate body language animations in real time from live speech by selecting segments from motion capture data of real people in conversation. The selection is driven by a hidden Markov model and uses prosody-based features extracted from speech. The training phase is fully automatic and does not require hand-labeling of input data, and the synthesis phase is efficient enough to run in real time on live microphone input. The results of a user study confirm that the proposed method is able to produce realistic and compelling body language.

Type of resource	text
Date created	2009-05

Author	Levine, Sergey V.
Advisor	Koltun, Vladlen
Advisor	Theobalt, Christian
Department	Stanford University. Department of Computer Science.

Subject	Human-computer interaction
Subject	Computer animation
Subject	Firestone Medal for Excellence in Undergraduate Research
Subject	Ben Wegbreit Prize for Best Undergraduate Honors Thesis in Computer Science
Genre	Thesis

Location	https://purl.stanford.edu/vh359gs8861

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License: This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

Preferred Citation: Levine, Sergey (2009). Body Language Animation Synthesis from Prosody. Stanford Digital Repository. Available at http://purl.stanford.edu/vh359gs8861

Undergraduate Theses, School of Engineering

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