This paper proposes a general probabilistic framework for shape-based modeling and classification of waveform data. A segmental hidden Markov model (HMM) is used to characterize w...
We present a semi-supervised source separation methodology to denoise speech by modeling speech as one source and noise as the other source. We model speech using the recently pro...
This paper addresses the problem of constructing good action selection policies for agents acting in partially observable environments, a class of problems generally known as Part...
We introduce in this paper a generalization of the widely used hidden Markov models (HMM's), which we name "structural hidden Markov models" (SHMM). Our approach is ...
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...