Learn More
This paper presents an overview of a state-of-the-art text-independent speaker verification system. First, an introduction proposes a modular scheme of the training and test phases of a speaker verification system. Then, the most commonly speech parameteriza-tion used in speaker verification, namely, cepstral analysis, is detailed. Gaussian mixture(More)
In this paper we describe the acquistion and content of a new large, realistic and challenging multi-modal database intended for training and testing multi-modal verification systems. The BANCA database was captured in four European languages in two modalities (face and voice). For recording, both high and low quality microphones and cameras were used. The(More)
—Probabilistic approaches can offer satisfactory solutions to source separation with a single channel, provided that the models of the sources match accurately the statistical properties of the mixed signals. However, it is not always possible to train such models. To overcome this problem, we propose to resort to an adaptation scheme for adjusting the(More)
We propose a new method to learn overcomplete dictionaries for sparse coding structured as unions of orthonormal bases. The interest of such a structure is manifold. Indeed, it seems that many signals or images can be modeled as the superimposition of several layers with sparse decompositions in as many bases. Moreover , in such dictionaries, the efficient(More)
We propose a new method to perform the separation of two sound sources from a single sensor. This method generalizes the Wiener filtering with locally stationary, non gaussian, parametric source models. The method involves a learning phase for which we propose three different algorithm. In the separation phase, we use a sparse non negative decomposition(More)
In this paper, we present an approach for speaker diarization based on segmentation followed by bottom-up clustering, where clusters are modeled using adapted Gaussian mixture models. We propose a novel inter-cluster distance in the model parameter space which is easily computable and which can both be used as the dissimilarity measure in the clustering(More)