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XSRP: eXtensible Steered Response Power

This repository contains the code for the paper:

Steered Response Power for Sound Source Localization: A Tutorial Review

The following functionality is currently implemented:

  • Conventional SRP-PHAT in the time domain (taking the DFT, applying the phase transform, followed by the IDFT) as described by Dibiase et al. [1]
  • Conventional SRP-PHAT in the frequency domain (same as above without the IDFT step) as described by Dibiase et al.
  • SRP in the time domain, using temporal cross-correlation without phase transform
  • Parabolic interpolation of the cross-correlation function in time
  • A simple Volumetric SRP approach which projects the average of N-closest correlation values instead of only the one associated with the microphone pair's Time Difference of Arrival (TDOA)
  • Grid creation functions for Positional Source Localization and Direction of Arrival (DOA) Estimation
  • Visualization tools

Installation

We recommend installing a Conda virtual environment using the provided environment.yml file. This will install all the required dependencies. Change directory to the xsrp folder and run the following commands:

  1. conda env create -f environment.yml
  2. conda activate xsrp

You can then optionally run the tests to verify that everything is working correctly:

  1. python -m pytest tests

You may want to check the images that were generated in the tests/temp folder.

xsrp's People

Contributors

egrinstein avatar

Stargazers

Luan V. Fiorio avatar AkenoSyuRi avatar Jisoo Myoung avatar math in avatar Monique Grinstein avatar  avatar Roal avatar  avatar oucxlw avatar taro avatar xiaobai  avatar changxu avatar  avatar

Watchers

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