Structured Hidden Markov Models (S-HMM) are a variant of Hierarchical Hidden Markov Models; it provides an abstraction mechanism allowing a high level symbolic description of the k...
We are interested in recovering aspects of vocal tract’s geometry and dynamics from auditory and visual speech cues. We approach the problem in a statistical framework based on ...
Athanassios Katsamanis, George Papandreou, Petros ...
We present a novel approach to speech-driven facial animation using a non-parametric switching state space model based on Gaussian processes. The model is an extension of the shar...
We investigate a recently proposed method for the analysis of oscillatory patterns in EEG data, with respect to its capacity of further quantifying processes on slower (< 1 Hz)...
Recent developments in technology and access have offered the opportunity to improve online learning environments through increased communication, interactivity among participants...