Speech and text driven HMM-based body animation synthesis
US8224652B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 26, 2008 |
| Grant date | Jul 17, 2012 |
| Priority date | — |
| Expiry date | May 14, 2031 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG10L13/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An “Animation Synthesizer” uses trainable probabilistic models, such as Hidden Markov Models (HMM), Artificial Neural Networks (ANN), etc., to provide speech and text driven body animation synthesis. Probabilistic models are trained using synchronized motion and speech inputs (e.g., live or recorded audio/video feeds) at various speech levels, such as sentences, phrases, words, phonemes, sub-phonemes, etc., depending upon the available data, and the motion type or body part being modeled. The Animation Synthesizer then uses the trainable probabilistic model for selecting animation trajectories for one or more different body parts (e.g., face, head, hands, arms, etc.) based on an arbitrary text and/or speech input. These animation trajectories are then used to synthesize a sequence of animations for digital avatars, cartoon characters, computer generated anthropomorphic persons or creatures, actual motions for physical robots, etc., that are synchronized with a speech output corresponding to the text and/or speech input.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.