AudioForge

Low-latency microphone audio processor with AI noise suppression, smart gating, Auto-EQ, and 10-band parametric EQ.

Current version: v1.7.0

Status

AudioForge is currently focused on Windows desktop use and portable distribution. It is optimized for personal use and small friend-group sharing.

Features

• AI noise suppression backends:
  • RNNoise (fast baseline)
  • DeepFilterNet LL (low-latency quality mode)
  • DeepFilterNet Standard (highest quality, higher latency)
• Smart gate modes:
  • Threshold-only gate
  • VAD-assisted gate
  • VAD-only gate
• 10-band parametric EQ with per-band frequency, gain, and Q controls
• Wideband de-esser with manual controls and auto amount mode
• Auto-EQ recording/analysis flow with validation and one-click apply/undo
• Dynamics:
  • Compressor (soft-knee, adaptive release, auto makeup support)
  • Hard limiter (final safety ceiling)
• Real-time metering and DSP telemetry:
  • Input/output level meters
  • Buffer and processing health metrics
  • Gate/VAD and gain-reduction indicators
• Preset save/load with migration support
• Latency calibration dialog for per device-pair compensation profiles

DSP Chain

Runtime processing chain:

Mic Input -> Pre-Filter (DC block + 80 Hz HP) -> Noise Gate -> Noise Suppression
-> De-Esser -> 10-Band EQ -> Compressor -> Limiter -> Output

Note: model latency labels describe suppressor and DSP behavior only. End-to-end round-trip latency also depends on device driver, buffer size, OS mixer path, and routing setup.

Quick Start (Windows)

Prerequisites

• Python 3.9+
• Rust 1.70+
• maturin

Build and run from source

git clone https://github.com/FueledByRedBull/audio-forge.git
cd audio-forge

python -m venv .venv
.\.venv\Scripts\python.exe -m pip install --upgrade pip
.\.venv\Scripts\python.exe -m pip install -e .[dev]

.\.venv\Scripts\python.exe -m maturin develop --release
.\.venv\Scripts\python.exe -m mic_eq

Optional Runtime Assets

Create models/ in repo root for runtime model discovery:

• models/DeepFilterNet3_ll_onnx.tar.gz
• models/DeepFilterNet3_onnx.tar.gz (optional if you only use LL)
• models/silero_vad.onnx (for VAD gate modes)

DeepFilter runtime library:

• df.dll in repo root (development)
• bundled next to AudioForge.exe for portable builds

You can also use environment variables:

• DEEPFILTER_MODEL_PATH
• VAD_MODEL_PATH

Build Portable EXE

Use the provided packaging script:

powershell -ExecutionPolicy Bypass -File .\build_exe.ps1

Output:

• dist\AudioForge\AudioForge.exe
• dist\AudioForge\df.dll (if present)
• dist\AudioForge\models\...

Create archive:

Compress-Archive -Path .\dist\AudioForge -DestinationPath .\AudioForge-win64-fresh.zip -CompressionLevel Optimal

Testing

Rust tests:

cd rust-core
cargo test -p mic_eq_core --tests

Python tests:

cd ..
.\.venv\Scripts\python.exe -m pytest python/tests -v

License

MIT License. See LICENSE.

Acknowledgments

• RNNoise by Jean-Marc Valin
• DeepFilterNet by Hendrik Schroter and contributors
• Silero VAD contributors