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 presents a non-parallel training algorithm for voice conversion based on feature transform Gaussian mixture model (FTGMM), which is a mixture model of joint density spa...
In this study, the generalized parametric spectral subtraction estimator is employed in the context of a ROVER speech enhancement framework to develop a robust phoneme class selec...
Recent and next-generation wireless broadcasting standards, such as DVB-T2 or DVB-NGH, are considering distributed multi-antenna transmission in order to increase bandwidth effic...
In a number of signal processing applications, problem formulations based on the 1 norm as a sparsity inducing signal prior lead to simple algorithms with good performance. Howeve...