In this paper, we examine the problem of overcomplete representations and provide new insights into the problem of stable recovery of sparse solutions in noisy environments. We es...
Consider a scenario where a distributed signal is sparse and is acquired by various sensors that see different versions. Thus, we have a set of sparse signals with both some commo...
We present the G.EV-VBR winning candidate codec recently selected by Question 9 of Study Group 16 (Q9/16) of ITU-T as a baseline for the development of a scalable solution for wid...
Milan Jelinek, Tommy Vaillancourt, A. Erdem Ertan,...
This paper presents a novel approach to language modeling for voice search based on the idea and method of statistical machine translation. We propose an n-gram based translation ...
In this paper we present a family of algorithms for estimating stream weights for dynamic Bayesian networks with multiple observation streams. For the 2 stream case, we present a ...
A parallel structure to do spectrum sensing in Cognitive Radio (CR) at sub-Nyquist rate is proposed. The structure is based on Compressed Sensing (CS) that exploits the sparsity o...
Recently, a novel and structural representation of speech was proposed [1, 2], where the inevitable acoustic variations caused by nonlinguistic factors are effectively removed fro...
Fundamental frequency contours for speech, as obtained by common pitch tracking algorithms, contain a great deal of fine detail that is unlikely to hold much perceptual significa...
This paper proposes a speech enhancement method for signals contaminated by room reverberation and additive background noise. The following conditions are assumed: (1) The spectra...