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Subband-based Single-channel Source Separation of Instantaneous Audio Mixtures
KTH, School of Electrical Engineering (EES), Sound and Image Processing.
Shahed University, Khalije Fars Highway, Teheran, Iran.
2009 (English)In: World Applied Sciences Journal, ISSN 1818-4952, Vol. 6, no 6, 784-792 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, a new algorithm is developed to separate the audio sources from a single instantaneous mixture. The algorithm is based on subband decomposition and uses a hybrid system of Empirical Mode Decomposition (EMD) and Principle Component Analysis (PCA) to construct artificial observations from the single mixture. In the separation stage of algorithm, we use Independent Component Analysis (ICA) to find independent components. At first the observed mixture is divided into a finite number of subbands through filtering with a parallel bank of FIR band-pass filters. Then EMD is employed to extract Intrinsic Mode Functions (IMFs) in each subband. By applying PCA to the extracted components, we find uncorrelated components which are the artificial observations. Then we obtain independent components by applying Independent Component Analysis (ICA) to the uncorrelated components. Finally, we carry out subband synthesis process to reconstruct fullband separated signals. The experimental results substantiate that the proposed method truly performs the task of source separation from a single instantaneous mixture.

Place, publisher, year, edition, pages
IDOSI Publications , 2009. Vol. 6, no 6, 784-792 p.
Keyword [en]
Blind source separation, independent component analysis, empirical mode decomposition, principle component analysis, single-channel audio source separation, subband decomposition
National Category
Signal Processing
URN: urn:nbn:se:kth:diva-49230OAI: diva2:459419
QC 20111220Available from: 2011-12-20 Created: 2011-11-25 Last updated: 2011-12-20Bibliographically approved

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