In a previous work, we developed a quasi-efficient maximum likelihood approach for blindly separating stationary, temporally correlated sources modeled by Markov processes. In this...
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
In this work, we model speech samples with the generalized Gamma distribution and evaluate the efficiency of such modelling for voice activity detection. Using a computationally i...
We present a method of classifying a pattern using information furnished by a ranked list of templates, rather than just the best matching template. We propose a parsimonious mode...
This paper presents an online feature selection and classification algorithm. The algorithm is implemented for impact acoustics signals to sort hazelnut kernels. The classifier, w...