DeepFilterNet3 — Streaming CoreML (GRU state I/O)
Same DeepFilterNet3 Neural Engine model as
aufklarer/DeepFilterNet3-CoreML,
re-exported with the three SqueezedGRU hidden states as explicit inputs and
outputs. Carrying those states across blocks gives glitch-free live
denoising (no GRU re-warm at every chunk boundary).
I/O
| Name | Shape | Role |
|---|---|---|
feat_erb |
[1, 1, T, 32] |
ERB features (T = 1…6000) |
feat_spec |
[1, 2, T, 96] |
Spec features (real/imag) |
h_enc |
[1, 1, 256] |
Encoder GRU state in |
h_erb |
[2, 1, 256] |
ERB-decoder GRU state in |
h_df |
[2, 1, 256] |
DF-decoder GRU state in |
erb_mask |
[1, 1, T, 32] |
ERB gain mask |
df_coefs |
[1, 5, T, 96, 2] |
Deep-filter coefficients |
h_enc_out / h_erb_out / h_df_out |
same as inputs | Updated GRU states |
Pass zeros for the first block; feed each *_out back as the next block's
input. STFT / ERB / iSTFT stay on CPU (same auxiliary.npz as the stock pack).
Files
| File | Description |
|---|---|
DeepFilterNet3.mlmodelc |
Pre-compiled CoreML (ANE) |
DeepFilterNet3.mlpackage |
Source package |
auxiliary.npz |
ERB filterbank, Vorbis window, norm states |
config.json |
Shapes / metadata |
License
- Weights: Apache-2.0 / MIT (Rikorose/DeepFilterNet3)
- Conversion: Apache-2.0
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