Fundamentals of speech recognition
Fundamentals of speech recognition
Dirichlet Free-Form Deformations and their Application to Hand Simulation
CA '97 Proceedings of the Computer Animation
MPEG-4 Compatible Faces from Orthogonal Photos
CA '99 Proceedings of the Computer Animation
Real Time Tracking and Modeling of Faces: An EKF-Based Analysis by Synthesis Approach
MPEOPLE '99 Proceedings of the IEEE International Workshop on Modelling People
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
Video Avatar: Embedded Video for Collaborative Virtual Environment
ICMCS '99 Proceedings of the IEEE International Conference on Multimedia Computing and Systems - Volume 2
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Neural Networks
A coupled HMM approach to video-realistic speech animation
Pattern Recognition
Audio-to-Visual Conversion Via HMM Inversion for Speech-Driven Facial Animation
SBIA '08 Proceedings of the 19th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
Dynamic Bayesian Network Inversion for Robust Speech Recognition
IEICE - Transactions on Information and Systems
Optimization of an image-based talking head system
EURASIP Journal on Audio, Speech, and Music Processing - Special issue on animating virtual speakers or singers from audio: Lip-synching facial animation
Face active appearance modeling and speech acoustic information to recover articulation
IEEE Transactions on Audio, Speech, and Language Processing - Special issue on multimodal processing in speech-based interactions
A multimodal probabilistic model for gesture--based control of sound synthesis
Proceedings of the 21st ACM international conference on Multimedia
Gesture--sound mapping by demonstration in interactive music systems
Proceedings of the 21st ACM international conference on Multimedia
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MPEG-4 standard allows composition of natural or synthetic video with facial animation. Based on this standard, an animated face can be inserted into natural or synthetic video to create new virtual working environments such as virtual meetings or virtual collaborative environments. For these applications, audio-to-visual conversion techniques can be used to generate a talking face that is synchronized with the voice. In this paper, we address audio-to-visual conversion problems by introducing a novel Hidden Markov Model Inversion (HMMI) method. In training audio-visual HMMs, the model parameters {λav} can be chosen to optimize some criterion such as maximum likelihood. In inversion of audio-visual HMMs, visual parameters that optimize some criterion can be found based on given speech and model parameters {λav}. By using the proposed HMMI technique, an animated talking face can be synchronized with audio and can be driven realistically. The HMMI technique combined with MPEG-4 standard to create a virtual conference system, named VIRTUAL-FACE, is introduced to show the role of HMMI for applications of MPEG-4 facial animation.