A Polynomial Eigenvalue Decomposition Music Approach for Broadband Sound Source Localization

Abstract

Direction of arrival (DoA) estimation for sound source localization is increasingly prevalent in modern devices. In this paper, we explore a polynomial extension to the multiple signal classification (MUSIC) algorithm, spatio-spectral polynomial (SSP)-MUSIC, and evaluate its performance when using speech sound sources. In addition, we also propose three essential enhancements for SSP-MUSIC to work with noisy reverberant audio data. This paper includes an analysis of SSP-MUSIC using speech signals in a simulated room for different noise and reverberation conditions and the first task of the LOCATA challenge. We show that SSP-MUSIC is more robust to noise and reverberation compared to independent frequency bin (IFB) approaches and improvements can be seen for single sound source localization at signal-to-noise ratios (SNRs) below 5 dB and reverberation times (T60s) larger than 0.7 s.

A Survey of Sound Source Localization with Deep Learning Methods

“…MUSIC and ESPRIT assume narrowband signals, although wideband extensions have been proposed, e.g. [82], [83]. Subspace methods are robust to noise and can produce highly accurate estimates, but are sensitive to reverberation.…”

Polynomial Eigenvalue Decomposition-Based Target Speaker Voice Activity Detection in the Presence of Competing Talkers

“…The approach uses an iterative polynomial matrix eigenvalue decomposition (PEVD) algorithm such as the family of second-order sequential best rotation (SBR2) [21,22] and sequential matrix diagonalization (SMD) approaches [23,24] in the time-domain or [25,26] in the frequency-domain. PEVD algorithms have been found useful for many broadband signal processing applications such as speech enhancement [27,28], source separation [29,30], source localizaton [31,32] and beamforming [33].…”

Enhanced Space-Time Covariance Estimation Based on a System Identification Approach

“…A number of application examples have been successfully addressed by the above algorithms, ranging, e.g., from coding [7], [21], beamforming [22], [23], angle of arrival estimation [24]- [26], speech enhancement [27]- [29], optimum precoder and equaliser resign for MIMO communications systems [30]- [33], and subspace scanning for weak transient signals [34]- [36].…”

“…This type of estimation for R[τ ] is possible e.g. in loudspeaker-microphone setup such as in [26]- [29]. For this purpose, we review the EVD of a space-time covariance matrix in Sec.…”