--- license: apache-2.0 library_name: coreml tags: - coreml - audio - speech-enhancement - noise-suppression - streaming - dpdfnet - 48khz --- # DPDFNet-8 48 kHz HR Core ML Stateful Core ML and MLX assets for CEVA's high-resolution **DPDFNet-8 48 kHz HR** speech-enhancement model. This is a separate architecture/profile from DPDFNet-4 and is supported by 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 | 48,000 Hz | | Input hop | 480 samples / 10 ms | | FFT | 960 samples | | DPRNN blocks | 8 | | Fixed algorithmic delay | 2,400 samples / 50 ms | ## Recommended model `DPDFNet8-48kHz-HR-Streaming-FP32.mlpackage` is the production default. Conversion validation against PyTorch produced effectively perfect output correlation (0.999999999998). FP16 explicit-state and resident-state variants are included for experimentation but are not selected automatically because their fidelity is lower. Current 60-second Swift/Core ML validation: 38.664 seconds total (1.55x real time), with 0.99999966 waveform correlation to official ONNX. Live p50/p95 model processing latency was 6.326/7.067 ms on the development Apple Silicon Mac. Device results vary. ## Swift usage ```swift import DeepFilterNetCoreML let enhancer = try await DeepFilterNetCoreMLStreamer.load( configuration: .init(variant: .dpdfNet8HighResolution) ) let output = try enhancer.processHop(input480Samples) ``` ## Files - `DPDFNet8-48kHz-HR-Streaming-FP32.mlpackage`: recommended explicit FP32 state graph. - `DPDFNet8-48kHz-HR-Streaming.mlpackage`: explicit FP16 state graph. - `DPDFNet8-48kHz-HR-Streaming-State.mlpackage`: Core ML `MLState` graph. - `DPDFNet8-48kHz-HR-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.