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This thesis aims to create an automated lip-synchronization system for real-time applications. Specifically, the system is required to be fast, consist of a limited number of keyframes with small memory requirements, and create fluid and believable animations that synchronize with text-to-speech engines as well as raw voice data.
The algorithms utilize traditional keyframe animation and a novel method of keyframe selection. Additionally, phoneme-to-keyframe mapping, synchronization, and simple blending rules are employed. The algorithms provide blending between keyframe images, borrow information from neighboring phonemes, accentuate phonemes b, p and m, differentiate between keyframes for phonemes with allophonic variations, and provide prosodromic variation by including emotion while speaking. The lip-sync animation synchronizes with multiple synthesized voices and human speech. A fast and versatile online real-time java chat interface is created to exhibit vivid facial animation.
Results show that the animation algorithms are fast and show accurate lip-synchronization. Additionally, surveys showed that the animations are visually pleasing and improve speech understandability 96% of the time. Applications for this project include internet chat capabilities, interactive teaching of foreign languages, animated news broadcasting, enhanced game technology, and cell phone messaging.
Senior Honors Thesis. Advisors: Lorie Loeb, Hany Farid, and Stephen Linder
Bibliographic citation for this report: [plain text] [BIB] [BibTeX] [Refer]
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William Pechter, "Synchronizing Keyframe Facial Animation to Multiple Text-to-Speech Engines and Natural Voice with Fast Response Time." Dartmouth Computer Science Technical Report TR2004-501, June 2004.
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