Similarity search, namely, finding approximate nearest neighborhoods, is the core of many large scale machine learning or vision applications. Recently, many research results dem...
In this paper, we consider power spectral density estimation of bandlimited, wide-sense stationary signals from sub-Nyquist sampled data. This problem has recently received attent...
Michael A. Lexa, Mike E. Davies, John S. Thompson,...
In context-dependent acoustic modeling, it is important to strike a balance between detailed modeling and data sufficiency for robust estimation of model parameters. In the past,...
In this paper we present a number of improvements that were recently made to the template based speech recognition system developed at ESAT. Combining these improvements resulted ...
Kris Demuynck, Dino Seppi, Hugo Van hamme, Dirk Va...
Sparse representations over redundant dictionaries offer an efficient paradigm for signal representation. Recently block-sparsity has been put forward as a prior condition for so...