# Fast and Robust 3-D Sound Source Localization with DSVD-PHAT

## TL;DR

This paper presents DSVD-PHAT, a new method for 3-D sound source localization that is robust to noise and significantly more computationally efficient, enabling real-time use on robots with limited processing power.

## Contribution

Introduction of DSVD-PHAT, a novel variant of SVD-PHAT, offering comparable noise robustness to GSVD-MUSIC but with 250 times less computational load.

## Key findings

- Achieves similar noise robustness as GSVD-MUSIC
- Reduces computational load by a factor of 250
- Suitable for real-time robotic applications

## Abstract

This paper introduces a variant of the Singular Value Decomposition with Phase Transform (SVD-PHAT), named Difference SVD-PHAT (DSVD-PHAT), to achieve robust Sound Source Localization (SSL) in noisy conditions. Experiments are performed on a Baxter robot with a four-microphone planar array mounted on its head. Results show that this method offers similar robustness to noise as the state-of-the-art Multiple Signal Classification based on Generalized Singular Value Decomposition (GSVD-MUSIC) method, and considerably reduces the computational load by a factor of 250. This performance gain thus makes DSVD-PHAT appealing for real-time application on robots with limited on-board computing power.