Subspace-Based Channel Shortening for the Blind Separation of Convolutive Mixtures
نویسندگان
چکیده
منابع مشابه
A RobustICA Based Algorithm for Blind Separation of Convolutive Mixtures
1 Abstract— We propose a frequency-domain method based on robust independent component analysis (RICA) to address the multichannel Blind Source Separation (BSS) problem of convolutive speech mixtures in highly reverberant environments. We impose regularization processes to tackle the ill-conditioning problem of the covariance matrix and to mitigate the performance degradation in the frequency...
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We propose utilizing subband-based blind source separation (BSS) for convolutive mixtures of speech. This is motivated by the drawback of frequency-domain BSS, i.e., when a long frame with a fixed long frame-shift is used to cover reverberation, the number of samples in each frequency decreases and the separation performance is degraded. In subband BSS, (1) by using a moderate number of subband...
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The problem of separating convolutive mixtures of unknown time series arises in several application domains, a prominent example being the so-called cocktail party problem, where we want to recover the speech signals of multiple speakers who are simultaneously talking in a room. The room may be reverberant due to reflections on the walls, i.e., the original source signals sq(n), q = 1, . . . , ...
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This paper introduces the blind source separation (BSS) of convolutive mixtures of acoustic signals, especially speech. A statistical and computational technique, called independent component analysis (ICA), is examined. By achieving nonlinear decorrelation, nonstationary decorrelation, or time-delayed decorrelation, we can find source signals only from observed mixed signals. Particular attent...
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ABSTRACT Using algorithmic complexity to perform blind source separation (BSS) was first proposed by Pajunen. This approach presents the advantage of taking the whole signal structure into account to achieve separation, whereas standard ICA-based methods only use either time-correlations or higher order statistics in order to do so. Another advantage of this approach is that no assumptions abou...
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ژورنال
عنوان ژورنال: IEEE Transactions on Signal Processing
سال: 2006
ISSN: 1053-587X
DOI: 10.1109/tsp.2006.880210