The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The model-based expectation maximization source separation and localization (MESSL) technique is a probabilistic time-frequency masking algorithm that achieves underdetermined blind source separation of speech sources. Using only two-channel recordings, MESSL clusters spectrogram points based on their interaural spatial cues. Gaussian mixture models (GMMs) are assumed for the interaural cues and their...
Blind sources separation (BSS) arises in a variety of fields in speech processing such as speech enhancement, speakers diarization and identification. Generally, methods for BSS consider several observations of the same recording. Single microphone analysis is the worst underdetermined case, but, it's also the more realistic one. In our approach, the autoregressive structure (short term prediction)...
In this paper, a novel algorithm is proposed to solve blind signal separation of nonlinear time-delayed mixtures of statistically independent sources. Both mixing and nonlinear distortion are included in the proposed model. Maximum Likelihood (ML) approach is developed to estimate the parameters in the model and this is formulated within the framework of the generalized Expectation-Maximization (EM)...
This paper considers the problem of blindly separating sub- and super-Gaussian sources from underdetermined mixtures. The underlying sources are assumed to be composed of two orthogonal components: one lying in the rowspace and the other in the nullspace of a mixing matrix. The mapping from the rowspace component to the mixtures by the mixing matrix is invertible using the pseudo-inverse of the mixing...
This paper addresses blind dereverberation techniques based on the inherent characteristics of speech signals. Two challenging issues for speech dereverberation involve decomposing reverberant observed signals into colored sources and room transfer functions (RTFs), and making the inverse filtering robust as regards acoustic and system noise. We show that short-time speech characteristics are very...
In this contribution, we propose an entirely novel family of flexible score functions for blind source separation (BSS), based on the generalized Gamma family of densities. An efficient maximum likelihood (ML) technique for estimating the parameters of such score functions in an adaptive BSS setup, is also put forward. Simulations indicate that the proposed density model can approximate speech signals...
A new algorithm for blind signal separation of speech signals that does not require pre-whitening is proposed in this paper. The algorithm is based on second order optimization using Riemannian geometry. The algorithm employs several practical approximations to the Hessian matrix of the maximum-likelihood blind separation cost function, to produce a computationally efficient algorithm that is capable...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.