Geometrically Constrained Decentralized Independent Vector Analysis for Distributed Microphone Arrays

2026-06-14

AI Summary

This work addresses the challenges of source separation in distributed microphone arrays, where performance is hindered by cross-array permutation inconsistency and strong inter-array dependencies. To overcome these limitations, the authors propose a geometry-constrained decentralized independent vector analysis (Dec-IVA) method that leverages direction-of-arrival (DOA) information to align sources across arrays and introduces a weakly dependent source model to reduce inter-array coupling. By integrating geometric constraints to resolve permutation ambiguity and incorporating power-based statistical exchange to enhance robustness against noise, the proposed approach achieves improved separation accuracy and cross-array consistency. Experimental results demonstrate that the method significantly outperforms existing techniques in both separation performance and alignment reliability across distributed arrays.

Abstract

This paper proposes a geometrically constrained decentralized independent vector analysis (GC-Dec-IVA) method for distributed microphone arrays. Recently proposed Dec-IVA method enables source separation by exchanging only power-related statistics to exploit cross-array information. However, this initial attempt often provides negligible improvement over applying IVA locally at each array, mainly due to the potential permutation inconsistency among arrays and the strong cross-array dependency implied by its source model. To address these limitations, we incorporate direction-of-arrival (DOA) information to derive GC-Dec-IVA, which mitigates permutation mismatch across arrays and enhances source alignment. Furthermore, a new source model is introduced to weaken cross-array dependency, improving robustness against permutation inconsistency in noisy environments. Experiments show the proposed method improves both the separation performance and cross-array permutation consistency.

Problem

• distributed microphone arrays
• permutation inconsistency
• cross-array dependency
• source separation
• independent vector analysis

Innovation

• geometric constraint
• decentralized independent vector analysis
• distributed microphone arrays
• direction-of-arrival
• permutation consistency