In this paper, we present our recent studies of F0 estimation from the surface electromyographic (EMG) data using a Gaussian mixture model (GMM)-based voice conversion (VC) techni...
Keigo Nakamura, Matthias Janke, Michael Wand, Tanj...
Speaker recognition using support vector machines (SVMs) with features derived from generative models has been shown to perform well. Typically, a universal background model (UBM)...
This paper seeks to increase the efficiency of background subtraction algorithms for motion detection. Our method uses a quadtree-base hierarchical framework that samples a small ...
This paper combines a parameter generation algorithm and a model optimization approach with the model-integration-based voice conversion (MIVC). We have proposed probabilistic int...
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...