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...
This paper describes a new approach to modeling duration for LVCSR using SCARF, a toolkit for speech recognition with segmental conditional random fields. We utilize SCARF’s abi...
Compressive sensing (CS) is a new approach for the acquisition and recovery of sparse signals that enables sampling rates significantly below the classical Nyquist rate. Based on...
Luisa F. Polania, Rafael E. Carrillo, Manuel Blanc...
Speech recognition applications are known to require a significant amount of resources (memory, computing power). However, embedded speech recognition systems, such as in mobile p...
Mohamed Bouallegue, Driss Matrouf, Georges Linares
Particle filters (PF) and auxiliary particle filters (APF) are widely used sequential Monte Carlo (SMC) techniques. In this paper we comparatively analyse the Sampling Importanc...