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An Automated System for Sound Localization Testing in Hearing-Impaired Listeners

An Automated System for Sound Localization Testing in Hearing-Impaired Listeners

Published on: March 13, 2026

A steered response power iterative method for high-accuracy acoustic source localization.

Amparo Marti¹, Maximo Cobos, Jose J Lopez

¹iTEAM Institute, Universitat Politècnica de València, 46022, Valencia, Spain.

The Journal of the Acoustical Society of America

|October 15, 2013

Summary

This summary is machine-generated.

This study introduces an iterative method for sound source localization using a modified steered response power (SRP) algorithm. The approach significantly reduces computational cost while maintaining high accuracy, making acoustic source identification more efficient.

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Area of Science:

Acoustics
Signal Processing
Computational Audition

Background:

Traditional source localization methods like steered response power (SRP) often rely on computationally expensive grid-search procedures.
Existing modified SRP algorithms offer improved robustness with coarser spatial grids, but further optimization is needed.

Purpose of the Study:

To present an iterative method for sound source localization based on a modified SRP algorithm.
To reduce the computational cost associated with high-accuracy source localization.

Main Methods:

An iterative decomposition approach using a modified SRP algorithm is proposed.
A coarse spatial grid is initially evaluated to identify a region of interest.
This region is then iteratively refined using a finer spatial grid.

Main Results:

The proposed iterative method achieves accuracy comparable to traditional fine-grid search methods.
A substantial reduction in the number of functional evaluations (computational cost) was observed.
The method demonstrates efficiency for acoustic source identification tasks.

Conclusions:

The iterative modified SRP method offers an efficient and accurate solution for sound source localization.
This approach mitigates the high computational burden of conventional grid-search techniques.
The findings contribute to more practical and scalable acoustic signal processing applications.