| --- |
| license: apache-2.0 |
| library_name: coreml |
| tags: |
| - coreml |
| - audio |
| - speech-enhancement |
| - noise-suppression |
| - streaming |
| - dpdfnet |
| --- |
| |
| # DPDFNet-4 Core ML |
|
|
| Stateful Core ML and MLX assets for **DPDFNet-4**, CEVA's 16 kHz real-time speech-enhancement model. This repository is the default DPDFNet-4 source for the [`DeepFilterNetCoreML`](https://github.com/kylehowells/DeepFilterNet-mlx) Swift product. |
|
|
| ## Origin |
|
|
| - Official implementation: [ceva-ip/DPDFNet](https://github.com/ceva-ip/DPDFNet) |
| - Official models: [Ceva-IP/DPDFNet](https://huggingface.co/Ceva-IP/DPDFNet) |
| - Paper: [DPDFNet](https://arxiv.org/abs/2512.16420) |
| - Swift runtime and conversions: [kylehowells/DeepFilterNet-mlx](https://github.com/kylehowells/DeepFilterNet-mlx) |
| - Conversion script: [`Scripts/Conversion/convert_dpdfnet_to_coreml.py`](https://github.com/kylehowells/DeepFilterNet-mlx/blob/feature/deepfilternet4/Scripts/Conversion/convert_dpdfnet_to_coreml.py) |
|
|
| ## Runtime contract |
|
|
| | Property | Value | |
| |---|---:| |
| | Sample rate | 16,000 Hz | |
| | Input hop | 160 samples / 10 ms | |
| | FFT | 320 samples | |
| | DPRNN blocks | 4 | |
| | Fixed algorithmic delay | 800 samples / 50 ms | |
|
|
| ## Recommended model |
|
|
| `DPDFNet4-Streaming-FP32.mlpackage` is the production default. Its conversion validation against the PyTorch graph produced 0.9999999999 output correlation. The FP16 explicit-state and resident-state variants are included for device-specific experiments but are not selected automatically because their fidelity is lower. |
|
|
| Current 60-second Swift/Core ML validation: 13.953 seconds total (4.30x real time), with 0.99999999 waveform correlation to official ONNX. Live p50/p95 model processing latency was 3.686/4.171 ms on the development Apple Silicon Mac. Device results vary. |
|
|
| ## Swift usage |
|
|
| ```swift |
| import DeepFilterNetCoreML |
| |
| let enhancer = try await DeepFilterNetCoreMLStreamer.load( |
| configuration: .init(variant: .dpdfNet4) |
| ) |
| let output = try enhancer.processHop(input160Samples) |
| ``` |
|
|
| ## Files |
|
|
| - `DPDFNet4-Streaming-FP32.mlpackage`: recommended explicit FP32 state graph. |
| - `DPDFNet4-Streaming.mlpackage`: explicit FP16 state graph. |
| - `DPDFNet4-Streaming-State.mlpackage`: Core ML `MLState` graph for supported OS versions. |
| - `DPDFNet4-initial-state-f32.bin`: canonical recurrent-state initialization. |
| - `config.json` and `model.safetensors`: matching Swift MLX/DSP model assets. |
| - `conversion-report.json`: graph-level validation and measured conversion latency. |
|
|
| ## License |
|
|
| Apache-2.0, matching the official CEVA DPDFNet repository. See `LICENSE` and the original project. |
|
|
