This repository contains an implementation of a Spherical Harmonics (SH) beamformer, designed to process raw audio signals from a spherical microphone array. The code allows for:
- Conversion of raw microphone signals into the SH domain
- Computation of the Maximum Directivity Beamformer in the SH domain
- Beamformed audio reconstruction for spatial audio applications
The repository includes real measured impulse responses of the spherical microphone array, which can be used to simulate audio recordings in real-world environments. These are located in data/RIRs/:
The package can be installed via pip after cloning the repository:
pip install -r requirements.txtWe provide a Jupyter notebook example.ipynb that demonstrates how to use the code and the provided RIRs to perform SH beamforming. This notebook shows a complete workflow from raw signals to beamformed outputs.
Some dependencies required for running the notebook or visualizing results are not included in requirements.txt to keep the main module lightweight. For full functionality in the notebook, you may need:
- IPython
- soundfile
- matplotlib
If you use this code in your research or projects, please cite our associated paper:
@INPROCEEDINGS{2029,
author = {Jaime Garcia-Martinez and Pablo Cabanas-Molero and Pedro Vera-Candeas and Julio J. Carabias-Orti and Antonio J. Munoz-Montoro},
booktitle = {2025 33rd European Signal Processing Conference (EUSIPCO)},
title = {Integrating High Order Ambisonics and Deep Learning for Advanced Instrument Separation in Spatial Audio Applications},
year = {2025},
volume = {},
number = {},
pages = {1253-1257},
isbn = {978-9-46-459362-4}
}Contributions are welcome! Please open an issue or submit a pull request if you'd like to improve the implementation.
This project is licensed under GPL v3. See the LICENSE file for details.