Publish validated DPDFNet-4 Core ML models

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LICENSE

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README.md

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+---
+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.

SHA256SUMS

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config.json

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+{
+  "model_version": "DPDFNet4",
+  "dpdfnet_profile": "16khz",
+  "sample_rate": 16000,
+  "fft_size": 320,
+  "hop_size": 160,
+  "min_nb_erb_freqs": 1,
+  "nb_erb": 32,
+  "nb_df": 96,
+  "dprnn_num_blocks": 4,
+  "dprnn_erb_bins": 8,
+  "dprnn_df_bins": 48,
+  "encoder_erb_strides": [
+    1,
+    2,
+    2,
+    1
+  ],
+  "decoder_erb_strides": [
+    1,
+    2,
+    2
+  ],
+  "feature_type": "erb",
+  "mask_type": "erb",
+  "df_order": 5,
+  "df_lookahead": 2,
+  "conv_lookahead": 2,
+  "conv_ch": 64,
+  "emb_hidden_dim": 256,
+  "emb_num_layers": 2,
+  "df_hidden_dim": 256,
+  "df_num_layers": 2,
+  "gru_groups": 1,
+  "linear_groups": 16,
+  "enc_linear_groups": 32,
+  "group_shuffle": false,
+  "enc_concat": true,
+  "df_gru_skip": "groupedlinear",
+  "conv_kernel": [
+    1,
+    3
+  ],
+  "convt_kernel": [
+    1,
+    3
+  ],
+  "conv_kernel_inp": [
+    3,
+    3
+  ],
+  "df_pathway_kernel_size_t": 5,
+  "lsnr_max": 35,
+  "lsnr_min": -15,
+  "decoder_upsample_type": "subpixel",
+  "source_checkpoint": "dpdfnet4.pth",
+  "source_repository": "https://github.com/ceva-ip/DPDFNet"
+}

conversion-report.json

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+{
+  "profile": "dpdfnet4",
+  "title": "DPDFNet-4",
+  "sample_rate": 16000,
+  "fft_size": 320,
+  "hop_size": 160,
+  "frequency_bins": 161,
+  "state_size": 52592,
+  "initial_state_file": "DPDFNet4-initial-state-f32.bin",
+  "explicit_model": "DPDFNet4-Streaming.mlpackage",
+  "explicit_fp32_model": "DPDFNet4-Streaming-FP32.mlpackage",
+  "resident_model": "DPDFNet4-Streaming-State.mlpackage",
+  "validation": {
+    "frames": 12,
+    "explicit_output": {
+      "correlation": 0.9927952038280239,
+      "rmse": 8.461416369186444e-05,
+      "normalized_rmse": 0.12002493727953133,
+      "maximum_absolute_error": 0.0009011869551613927
+    },
+    "explicit_state": {
+      "correlation": 0.9999993603846058,
+      "rmse": 0.0020585762078087354,
+      "normalized_rmse": 0.0011448884309491864,
+      "maximum_absolute_error": 0.16117095947265625
+    },
+    "explicit_fp32_output": {
+      "correlation": 0.9999999999347807,
+      "rmse": 8.052760250805834e-09,
+      "normalized_rmse": 1.1422816250360271e-05,
+      "maximum_absolute_error": 9.815266821533442e-08
+    },
+    "explicit_fp32_state": {
+      "correlation": 1.0,
+      "rmse": 1.302360852194665e-07,
+      "normalized_rmse": 7.243151198108724e-08,
+      "maximum_absolute_error": 3.814697265625e-06
+    },
+    "resident_output": {
+      "correlation": 0.992286283428231,
+      "rmse": 8.743101633543035e-05,
+      "normalized_rmse": 0.1240206343013786,
+      "maximum_absolute_error": 0.0009785620495676994
+    },
+    "resident_state": {
+      "correlation": 0.999999357389139,
+      "rmse": 0.002063418651997784,
+      "normalized_rmse": 0.0011475815828026514,
+      "maximum_absolute_error": 0.16117095947265625
+    },
+    "explicit_warm_median_ms": 2.579270483693108,
+    "explicit_fp32_warm_median_ms": 2.4225005181506276,
+    "resident_warm_median_ms": 2.4513959942851216
+  }
+}

model.safetensors

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