PCA-ICA Based Acoustic Ambient Extraction

Authors(2) :-G. Rajitha, K. Upendra Raju

Primary-ambient extraction (PAE) has been playing an important role in spatial audio analysis-synthesis. Based on the spatial features, PAE decomposes a signal into primary and ambient components, which are then rendered separately. PAE is performed in sub band domain for complex input signals having multiple point-like sound sources. However, the performance of PAE approaches and their key influences for such signals have not been well-studied so far. In this paper, we conducted a study on frequency-domain PAE using principal component analysis (PCA) and independent component analysis (ICA) in the case of multiple sources. We found that the partitioning of the frequency bins is very critical in PAE. Simulation results reveal that the proposed top-down adaptive partitioning method achieves superior performance as compared to the conventional partitioning methods.

Authors and Affiliations

G. Rajitha
M.Tech (Embedded Systems), Department of ECE, SVCE, Tirupati, Andhra Pradesh, India
K. Upendra Raju
Assistant Professor, Department of ECE, SVCE, Tirupati, Andhra Pradesh, India

Primary Ambient Extraction (PAE), Ambient Phase, Spatial Audio, Sparsity, Principal Component analysis (PCA), Independent Component Analysis (ICA), Frequency Domain.

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Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 51-59
Manuscript Number : CSEIT1726324
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

G. Rajitha, K. Upendra Raju, "PCA-ICA Based Acoustic Ambient Extraction ", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.51-59, January-February.2018
URL : http://ijsrcseit.com/CSEIT1726324

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