In this paper, we describe a novel speaker adaptation algorithm based on Gaussian mixture weight adaptation. A small number of latent speaker vectors are estimated with non-negati...
We present a computational framework capable of labeling the effort of an action corresponding to the perceived level of exertion by the performer (low ? high). The approach initi...
We describe the first tractable Gibbs sampling procedure for estimating phrase pair frequencies under a probabilistic model of phrase alignment. We propose and evaluate two nonpar...
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
While there is a lot of empirical evidence showing that traditional rule learning approaches work well in practice, it is nearly impossible to derive analytical results about thei...