APSIPA Transactions on Signal and Information Processing > Vol 13 > Issue 1

Self-Rotation-Robust Online-Independent Vector Analysis with Sound Field Interpolation on Circular Microphone Array

Taishi Nakashima, Tokyo Metropolitan University, Japan, taishi@ieee.org , Yukoh Wakabayashi, Toyohashi University of Technology, Japan, Nobutaka Ono, Tokyo Metropolitan University, Japan
 
Suggested Citation
Taishi Nakashima, Yukoh Wakabayashi and Nobutaka Ono (2024), "Self-Rotation-Robust Online-Independent Vector Analysis with Sound Field Interpolation on Circular Microphone Array", APSIPA Transactions on Signal and Information Processing: Vol. 13: No. 1, e5. http://dx.doi.org/10.1561/116.00000163

Publication Date: 26 Feb 2024
© 2024 T. Nakashima, Y. Wakabayashi and N. Ono
 
Subjects
 
Keywords
Blind source separationonline-independent vector analysiscircular microphone arraysound field interpolation
 

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This is published under the terms of CC BY-NC.

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In this article:
Introduction 
Problem Formulation 
Conventional Methods 
Proposed Method 
Experimental Validation 
Conclusion 
References 

Abstract

In this paper, we propose an online blind source separation (BSS) method that is robust against the self-rotation of microphone arrays. Online auxiliary-function-based independent vector analysis (OIVA) is one of the promising methods for real-time BSS. One major issue of real-time BSS is robustness against the movements of sources or microphones. Parameter re-estimation is necessary if such changes occur during processing. OIVA is robust against smooth movements of sources and achieves high separation performance. However, OIVA should perform better against rapid movements of microphones. In this study, we exploit sound field interpolation (SFI) for circular microphone arrays (CMAs) with OIVA. SFI cancels out the rotation of a CMA, enabling us to apply BSS without parameter re-estimation. We propose two methods: a combination of SFI and OIVA for preprocessing and a method using parameter transformations for practical applications. Simulation experiments confirmed that SFI improves the robustness of OIVA in situations where the microphone is rotating.

DOI:10.1561/116.00000163