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Implementation of Spherical Acoustic Spatial Entropy (SASE), Energy Entropy (EE) and Spectral Entropy (SE) as estimators of acoustic scene complexity
Guide and documentation of 3D printable open headphones
Object-based audio engine and codec pack with Dolby Atmos rendering, room correction, HRTF, one-click Unity audio takeover, and much more.
The Binaural Rendering Toolbox (BRT) is a set of software libraries, applications, and definitions aimed as a virtual laboratory for psychoacoustic experimentation. The BRT is developed in the fram…
Binaural to Ambisonics Conversion Pipeline
A Python library for acousticians.
Quality Assessment for SpaTial Audio network.A DNN-based Quality Metric for Spatial Audio (HOA, binaural)
A Python library for audio data augmentation. Useful for making audio ML models work well in the real world, not just in the lab.
AI agents running research on single-GPU nanochat training automatically
FLAMO: Frequency-sampling Library for Audio-Module Optimization
Open-Unmix - Music Source Separation for PyTorch
Advanced Signal Processing Notebooks and Tutorials
A curated collection of automation blueprints for Home Assistant.
Upload of several code examples to be used with the audio-appkits (e.g. audio-loopback through aurix, usage of class-D amplifier, usage of PDM microphones, small ethernet-streaming examples, etc…)
The PyTorch-based audio source separation toolkit for researchers
Toolbox for Evaluation of AEC/AES Systems
HARP: A Large-Scale Higher-Order Ambisonic Room Impulse Response Dataset
Analyze, visualize, and process sound field data recorded by spherical microphone arrays.
A Python Library for Full Reference Binaural Fidelity Testing, Visualization & Feature Generation
An Open-Source Library for RIR Synthesis and Analysis in PyTorch based on FLAMO
DAW focused plugins and apps relating to mixing Mach1 Spatial multichannel mixes
Spatial Audio rendering library, with Ambisonic encoding/decoding, binauralization in C++
Tutorial on using machine learning for acoustics. This tutorial covers a wide range of machine learning approaches for acoustic applications.