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TASLP
2008
102views more  TASLP 2008»
14 years 9 months ago
Acoustic Source Separation of Convolutive Mixtures Based on Intensity Vector Statistics
Various techniques have previously been proposed for the separation of convolutive mixtures. These techniques can be classified as stochastic, adaptive, and deterministic. Stochast...
Banu Gunel, Hüseyin Hacihabiboglu, Ahmet M. K...
INTERSPEECH
2010
14 years 4 months ago
Sparse component analysis for speech recognition in multi-speaker environment
Sparse Component Analysis is a relatively young technique that relies upon a representation of signal occupying only a small part of a larger space. Mixtures of sparse components ...
Afsaneh Asaei, Hervé Bourlard, Philip N. Ga...
ICMCS
2006
IEEE
98views Multimedia» more  ICMCS 2006»
15 years 3 months ago
On the Use of Time-Frequency Representation in Multicomponent Signal Separation
In this paper, we address the problem of separating unknown multicomponent signals from their instantaneous mixtures. Using linear time-frequency (TF) representation of the mixtur...
Braham Barkat, Farook Sattar, Karim Abed-Meraim
ICASSP
2010
IEEE
14 years 9 months ago
Under-determined convolutive blind source separation using spatial covariance models
This paper deals with the problem of under-determined convolutive blind source separation. We model the contribution of each source to all mixture channels in the time-frequency d...
Ngoc Q. K. Duong, Emmanuel Vincent, Rémi Gr...
TASLP
2010
159views more  TASLP 2010»
14 years 4 months ago
Under-Determined Reverberant Audio Source Separation Using a Full-Rank Spatial Covariance Model
This article addresses the modeling of reverberant recording environments in the context of under-determined convolutive blind source separation. We model the contribution of each ...
Ngoc Q. K. Duong, Emmanuel Vincent, Rémi Gr...