Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
The article contributes a derivation of variational Bayes for a large class of topic models by generalising from the well-known model of latent Dirichcation. For an abstraction of ...
This paper presents the use of online Variational Bayes method for online Voice Activity Detection (VAD) in an unsupervised context. In conventional VAD, the final step often rel...
David Cournapeau, Shinji Watanabe, Atsushi Nakamur...
This paper addresses the problem of Voice Active Detection (VAD) in noisy environments. We introduce Variational Bayes approach to EM for classification to replace the heuristic ...