Virtual Character Performance From Speech
Date
2013Author
Marsella, Stacy
Xu, Yuyu
Lhommet, Margaux
Feng, Andrew
Scherer, Stefan
Shapirok, Ari
Metadata
Show full item recordAbstract
We demonstrate a method for generating a 3D virtual character performance from the audio signal by inferring the acoustic and semantic properties of the utterance. Through a prosodic analysis of the acoustic signal, we perform an analysis for stress and pitch, relate it to the spoken words and identify the agitation state. Our rule-based system performs a shallow analysis of the utterance text to determine its semantic, pragmatic and rhetorical content. Based on these analyses, the system generates facial expressions and behaviors including head movements, eye saccades, gestures, blinks and gazes. Our technique is able to synthesize the performance and generate novel gesture animations based on coarticulation with other closely scheduled animations. Because our method utilizes semantics in addition to prosody, we are able to generate virtual character performances that are more appropriate than methods that use only prosody. We perform a study that shows that our technique outperforms methods that use prosody alone.
BibTeX
@inproceedings {10.1145:2485895.2485900,
booktitle = {Eurographics/ ACM SIGGRAPH Symposium on Computer Animation},
editor = {Theodore Kim and Robert Sumner},
title = {{Virtual Character Performance From Speech}},
author = {Marsella, Stacy and Xu, Yuyu and Lhommet, Margaux and Feng, Andrew and Scherer, Stefan and Shapirok, Ari},
year = {2013},
publisher = {ACM SIGGRAPH / Eurographics Association},
ISSN = {1727-5288},
ISBN = {978-1-4503-2132-7},
DOI = {10.1145/2485895.2485900}
}
booktitle = {Eurographics/ ACM SIGGRAPH Symposium on Computer Animation},
editor = {Theodore Kim and Robert Sumner},
title = {{Virtual Character Performance From Speech}},
author = {Marsella, Stacy and Xu, Yuyu and Lhommet, Margaux and Feng, Andrew and Scherer, Stefan and Shapirok, Ari},
year = {2013},
publisher = {ACM SIGGRAPH / Eurographics Association},
ISSN = {1727-5288},
ISBN = {978-1-4503-2132-7},
DOI = {10.1145/2485895.2485900}
}