Skip to main content

A controllable, end-to-end API for soundscape synthesis across ray-traced & real-world measured acoustics

Project description

AudibleLight

A Controllable, End-to-End API for Soundscape Synthesis Across Ray-Traced & Real-World Measured Acoustics

Docs Status Tests Status Codecov report Platform: Linux Python: 3.10 Code style: black Pull requests: welcome CC BY 4.0

⚠️ WARNING: This project is currently under heavy development. We have done our due diligence to ensure that it works as expected. However, if you encounter any errors, please open an issue and let us know.

Contents

What is AudibleLight?

AudibleLight is a unified API for soundscape synthesis supporting ray-traced, real-world, and parametric RIR generation. It enables flexible microphone array modeling and dynamic, fully annotated source trajectories within a single workflow. It is built upon SpatialScaper, SoundSpaces and Pyroomacoustics for scalable soundscape generation with unprecedented acoustic diversity.

AudibleLight is developed by researchers at the Centre for Digital Music, Queen Mary University of London in collaboration with Meta Reality Labs.

Installation:

Prerequisites

  • python3.10 or above (tested up to python3.12)
  • A modern Linux distro: current versions of Ubuntu and Red Hat have been tested and confirmed to work.
    • Using another OS? Let us know so we can add it here!

If you're looking to develop AudibleLight, you'll also need to install:

  • git
  • poetry
  • make

Install via pypi

For non-development installs, the simplest way to install AudibleLight is via pypi:

sudo apt install -y libsox-dev libsox-fmt-all freeglut3-dev pandoc
pip install audiblelight

Install via the command line

git clone https://github.com/AudibleLight/AudibleLight.git
cd AudibleLight
make install

Download data

We provide several helper scripts to download and prepare data (3D meshes, sofa files, audio files) that may be useful in AudibleLight.

You can run these scripts directly from the Python interpreter:

from audiblelight.download_data import download_fsd

download_fsd(path="path/to/save/fsd", cleanup=True)

Alternatively, for a development install, you can run them from the command line:

poetry run python scripts/download_data/download_fsd.py --path path/to/save/fsd --cleanup

From a development install, you can also run all download scripts at once using the Makefile:

make download

For further information, see scripts/download_data/README.md.

Usage

See the quickstart guide for help getting started with dataset generation in AudibleLight

Script

We include scripts to generate large datasets for common tasks relating to spatial soundscape synthesis.

To generate a dataset for sound event localization and detection (SELD) that conforms with the DCASE2023 task 3 format, run:

poetry run python scripts/seld/generate_dataset.py

To see the available arguments that this script takes, add the --help argument

If you want to generate custom datasets (or want to implement AudibleLight in a larger pipeline), please see the quickstart, tutorials, and API documentation.

Contributions

... are welcome! Please make a PR or take a look at the open issues.

Running the tests

Before making a PR, ensure that you run the pre-commit hooks and tests:

make fix
make tests

Roadmap

Citation

If you refer to any aspect of this work, please cite the following paper:

View citation
@inproceedings{cheston2025audiblelight,
    title={AudibleLight (RC): A Controllable, End-to-End API for Soundscape Synthesis Across Ray-Traced & Real-World Measured Acoustics}, 
    author={Cheston, Huw and Stepien, Adrian, and Azcarreta, Juan and Roman, Adrian S. and Chen, Chuyang and Roman, Iran R.},
    year={2025},
    booktitle={DMRN+ 20: Digital Music Research Network One-Day Workshop 2025}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

audiblelight-0.1.1.tar.gz (139.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

audiblelight-0.1.1-py3-none-any.whl (153.7 kB view details)

Uploaded Python 3

File details

Details for the file audiblelight-0.1.1.tar.gz.

File metadata

  • Download URL: audiblelight-0.1.1.tar.gz
  • Upload date:
  • Size: 139.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.0

File hashes

Hashes for audiblelight-0.1.1.tar.gz
Algorithm Hash digest
SHA256 b0ae01341980278dfe45317e7956473c71da523f981e79439c67d2f19ee64f3d
MD5 9f413c4454d173a335f6eb768eee31f8
BLAKE2b-256 740b7eabcf144a224bc7ac7bf370a544730e50b935ec73a85aa3592b515f7b02

See more details on using hashes here.

File details

Details for the file audiblelight-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: audiblelight-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 153.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.10.0

File hashes

Hashes for audiblelight-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 98fa58ccb68f37f759dbff868e18ffeab922919bb576e38df499d7a0c91c86c4
MD5 6ef2a4eaed9ddc8306a30c087dbe10ed
BLAKE2b-256 7488371e34a6b9311b811df7bd8611f9ea67623e131642303d34a51a5323e71a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page