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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.
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