A new Bayesian model is proposed, integrating dictionary learning and topic modeling into a unified framework. The model is applied to cluster multiple images, and a subset of th...
Lingbo Li, Mingyuan Zhou, Eric Wang, Lawrence Cari...
In voice analysis, the parameters estimation of a glottal model, an analytic description of the deterministic component of the glottal source, is a challenging question to assess ...
Iterative decoding is considered in this paper from an optimization point of view. Starting from the optimal maximum likelihood decoding, a (tractable) approximate criterion is de...
This paper addresses online learning of reference object distribution in the context of two hybrid tracking schemes that combine the mean shift with local point feature correspond...
Image reconstruction problems in radio astronomy and other fields like biomedical imaging are often ill-posed and some form of regularization is required. This imposes user speci...
Prior models of speech have been used in robust automatic speech recognition to enhance noisy speech. Typically, a single prior model is trained by pooling the entire training dat...
Arun Narayanan, Xiaojia Zhao, DeLiang Wang, Eric F...
This paper presents a discriminative training (DT) approach to irrelevant variability normalization (IVN) based training of feature transforms and hidden Markov models for large v...
In this paper, we present a novel non-data aided method for phase recovery in both square and cross quadrature amplitude modulation (QAM) communication systems, based on character...
The proportionate normalized least-mean squares (PNLMS) adaptation algorithm exploits the sparse nature of acoustic impulse responses and assigns adaptation gain proportional to t...
Currently, the statistical framework based on Hidden Markov Models (HMMs) plays a relevant role in speech synthesis, while voice conversion systems based on Gaussian Mixture Model...