Underdetermined source separation using mixtures of warped laplacians
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Glimpsing IVA: a framework for overcomplete/complete/undercomplete convolutive source separation
IEEE Transactions on Audio, Speech, and Language Processing - Special issue on processing reverberant speech: methodologies and applications
A directional laplacian density for underdetermined audio source separation
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part I
Two-microphone multi-speaker localization based on a Laplacian Mixture Model
Digital Signal Processing
DOA Estimation for Multiple Sparse Sources with Arbitrarily Arranged Multiple Sensors
Journal of Signal Processing Systems
Modulation domain blind speech separation in noisy environments
Speech Communication
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In this paper, we explore the problem of sound source separation and identification from a two-sensor instantaneous mixture. The estimation of the mixing and the sources is performed using Laplacian mixture models (LMM). The proposed algorithm fits the model using batch processing of the observed data and performs separation using either a hard or a soft decision scheme. An extension of the algorithm to online source separation, where the samples are arriving in a real-time fashion, is also presented. The online version demonstrates several promising source separation possibilities in the case of nonstationary mixing.