--- license: mit library_name: mlx tags: - mlx - audio - speech-enhancement - noise-suppression - deepfilternet - apple-silicon base_model: DeepFilterNet/DeepFilterNet2 pipeline_tag: audio-to-audio --- # DeepFilterNet2 — MLX MLX-compatible weights for [DeepFilterNet2](https://github.com/Rikorose/DeepFilterNet), a real-time speech enhancement model that suppresses background noise from audio. This is a direct conversion of the original PyTorch weights to `safetensors` format for use with [MLX](https://github.com/ml-explore/mlx) on Apple Silicon. ## Origin - **Original model:** [DeepFilterNet2](https://github.com/Rikorose/DeepFilterNet) by Hendrik Schroeter - **Paper:** [DeepFilterNet2: Towards Real-Time Speech Enhancement on Embedded Devices for Full-Band Audio](https://arxiv.org/abs/2205.05474) - **License:** MIT (same as the original) - **Conversion:** PyTorch -> `safetensors` via the included `convert_deepfilternet.py` script No fine-tuning or quantization was applied. Weights are converted directly from the original checkpoint. ## Files | File | Description | |---|---| | `config.json` | Model architecture configuration | | `model.safetensors` | Pre-converted weights (~8.9 MB, float32) | | `convert_deepfilternet.py` | Conversion script (PyTorch -> MLX safetensors) | ## Model Details | Parameter | Value | |---|---| | Sample rate | 48 kHz | | FFT size | 960 | | Hop size | 480 | | ERB bands | 32 | | DF bins | 96 | | DF order | 5 | | Embedding hidden dim | 256 | ## Usage ### Swift (mlx-audio-swift) ```swift import MLXAudioSTS let model = try await DeepFilterNetModel.fromPretrained("iky1e/DeepFilterNet2-MLX") let enhanced = try model.enhance(audioArray) ``` ### Python (mlx-audio) ```python from mlx_audio.sts.models.deepfilternet import DeepFilterNetModel model = DeepFilterNetModel.from_pretrained("iky1e/DeepFilterNet2-MLX") enhanced = model.enhance("noisy.wav") ``` ## Converting from PyTorch ```bash python convert_deepfilternet.py \ --input /path/to/DeepFilterNet2 \ --output ./DeepFilterNet2-MLX \ --name DeepFilterNet2 ``` ## Citation ```bibtex @inproceedings{schroeter2022deepfilternet2, title = {{DeepFilterNet2}: Towards Real-Time Speech Enhancement on Embedded Devices for Full-Band Audio}, author = {Schr{\"o}ter, Hendrik and Escalante-B., Alberto N. and Rosenkranz, Tobias and Maier, Andreas}, booktitle={17th International Workshop on Acoustic Signal Enhancement (IWAENC 2022)}, year = {2022}, } ```