Skip to main content

An Open-Source Library for RIR Synthesis and Analysis in PyTorch based on FLAMO

Project description

FLARE

LBDP | poster

An Open-Source Library for Room Impulse Response Synthesis and Analysis in PyTorch based on FLAMO.

This library will be presented at the AES Conference on Artificial Intelligence and Machine Learning for Audio (AIMLA), Queen Mary University, London (UK), 8-10 September 2025

More information soon!

Installation

pip install flareverb

Project Structure

src/flareverb/
├── reverb.py            # Core FDN implementations
├── generate.py          # RIR generation utilities
├── sampling.py          # Delays, gains, and filters sampling
├── analysis.py          # Acoustic analysis functions
├── utils.py             # Utility functions
├── config/              # Configuration modules
└── data/                # Data folder (contains absorption coefficients)

Configuration

FLARE uses Pydantic models for configuration management. The main configuration classes are:

FDNConfig

Core FDN configuration parameters:

  • N: Number of delay lines (default: 6)
  • fs: Sampling frequency in Hz (default: 48000)
  • in_ch / out_ch: Input/output channels (default: 1)
  • delay_range_ms: Delay lengths range in milliseconds (default: [20.0, 50.0])
  • delay_log_spacing: Use logarithmic spacing for delays (default: False)
  • early_reflections_type: Type of early reflections - 'gain', 'FIR', or None (default: None)
  • drr: Direct-to-reverberant ratio (default: 0.25, auto-set to 0 if early_reflections_type is None)
  • gain_init: Gain initialization - 'randn' or 'uniform' (default: 'randn')

FDNAttenuation

Attenuation filter configuration:

  • attenuation_type: Filter type - 'homogeneous', 'geq', or 'first_order_lp' (default: 'homogeneous')
  • attenuation_range: RT range in seconds when attenuation_param not given (default: [0.5, 3.5])
  • t60_center_freq: Center frequencies for T60 (default: [63, 125, 250, 500, 1000, 2000, 4000, 8000])
  • rt_nyquist: RT at Nyquist frequency for first-order filters (default: 0.2)

FDNMixing

Mixing matrix configuration:

  • mixing_type: Matrix type - 'orthogonal', 'householder', 'hadamard', or 'rotation' (default: 'orthogonal')
  • is_scattering: Use scattering matrix (default: False)
  • is_velvet_noise: Use velvet noise (default: False)
  • n_stages: Number of scattering stages (default: 3)

GFDNConfig

Grouped FDN configuration (inherits from FDNConfig):

  • n_groups: Number of groups (default: 2)
  • coupling_angles: Inter-group coupling angles (default: [0.0])
  • mixing_angles: Intra-group mixing angles (default: [0.0, 0.0])

Requirements

  • Python >= 3.10
  • PyTorch
  • FLAMO >= 0.1.13
  • pydantic
  • pyyaml
  • pandas

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit issues and pull requests.

Links

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

flareverb-0.0.4.tar.gz (26.8 MB view details)

Uploaded Source

Built Distribution

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

flareverb-0.0.4-py3-none-any.whl (36.6 kB view details)

Uploaded Python 3

File details

Details for the file flareverb-0.0.4.tar.gz.

File metadata

  • Download URL: flareverb-0.0.4.tar.gz
  • Upload date:
  • Size: 26.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.15

File hashes

Hashes for flareverb-0.0.4.tar.gz
Algorithm Hash digest
SHA256 7ecee64ddd8978920eb390b01374cf6d6a506051b50132c110e3550dcade036c
MD5 3f3dd9b4a98cae882fca963513615118
BLAKE2b-256 0061c3f8c85cb417dfaa2eef18df893ba2aea9cace054fa425af89b692326141

See more details on using hashes here.

File details

Details for the file flareverb-0.0.4-py3-none-any.whl.

File metadata

  • Download URL: flareverb-0.0.4-py3-none-any.whl
  • Upload date:
  • Size: 36.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.15

File hashes

Hashes for flareverb-0.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 d8b19562206370b20f10afb95374ed3fce877ad8162dcb2a0d8d14cf37d9a863
MD5 4d476248bb66a89c8a22423bb973fede
BLAKE2b-256 1533776fdbe13b112bea857b3ba3a0213c86c228c664d68acb6dd7ad2d177a94

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