Non-negative matrix factorization-based subband decomposition for acoustic source localization

TL;DR

This paper introduces a novel NMF-based subband decomposition method for acoustic source localization that improves accuracy in noisy and reverberant environments by emphasizing source-dominant frequency bins.

Contribution

The paper presents a new NMF-based subband decomposition technique in the frequency spatial domain for more accurate acoustic source localization using microphone arrays.

Findings

Outperforms conventional algorithms in simulated and real noisy environments.

Effective in reverberant conditions with improved localization accuracy.

Utilizes NMF to extract delay basis vectors and subband information.

Abstract

A novel non-negative matrix factorization (NMF) based subband decomposition in frequency spatial domain for acoustic source localization using a microphone array is introduced. The proposed method decomposes source and noise subband and emphasises source dominant frequency bins for more accurate source representation. By employing NMF, delay basis vectors and their subband information in frequency spatial domain for each frame is extracted. The proposed algorithm is evaluated in both simulated noise and real noise with a speech corpus database. Experimental results clearly indicate that the algorithm performs more accurately than other conventional algorithms under both reverberant and noisy acoustic environments.