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README.md
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# LocalVQE β Local Voice Quality Enhancement
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Real-time joint acoustic echo cancellation (AEC), noise suppression (NS),
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**
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mask) is based on **DeepVQE** (Indenbom et al., Interspeech 2023 β *DeepVQE:
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Real Time Deep Voice Quality Enhancement for Joint Acoustic Echo Cancellation,
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Noise Suppression and Dereverberation*,
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[arXiv:2306.03177](https://arxiv.org/abs/2306.03177)). This fork replaces
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STFT with a DCT-II analysis/synthesis filterbank for quantisation-aware
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local CPU/GPU inference, swaps the GRU bottleneck for S4D, and ships a
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streaming GGML graph so the model can run on an F32 CPU pipeline in under
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2 ms/frame at 16 kHz.
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(DCT-II in-graph, GGML runtime, training pipeline, AEC fine-tune recipe)
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is original to this repo.
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**Authors:**
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- Richard Palethorpe ([richiejp](https://github.com/richiejp))
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- Claude (Anthropic)
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**Project source:** <https://github.com/richiejp/LocalVQE>
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## Files
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## Usage (GGML / C++ / Go)
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```bash
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cd ggml && cmake -B build -DCMAKE_BUILD_TYPE=Release && cmake --build build -j
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./build/bin/localvqe localvqe-v1-f32.gguf \
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--in-wav mic.wav ref.wav --out-wav enhanced.wav
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```
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Per-frame wall time on Zen4 (24 threads): ~1.66 ms (9.6Γ realtime at
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16 kHz / 256-sample hop).
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## Validation
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Best checkpoint of the published v1 F32 weights (`localvqe-v1-f32.gguf`), evaluated
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on a 1 000-clip validation split mixing DNS5-synthesised scenes and ICASSP
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AEC Challenge synthetic data; AECMOS over a 100-clip sub-sample.
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| Metric | Overall | Single-talk far-end | Double-talk |
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|---|---:|---:|---:|
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| ERLE | β | **+52.2 dB** | β |
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| AECMOS echo (β) | 4.36 | 4.46 | 4.33 |
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| AECMOS degradation (β) | 4.83 | 5.00 | 4.78 |
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ERLE is only meaningful on single-talk far-end (mic = pure echo); overall
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and double-talk ERLE are confounded by near-end speech and are omitted.
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DNSMOS OVRL is deliberately omitted: our P.808 scores (~2.0) contradict
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informal listening of the single-talk far-end output, which is audibly
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near-silent. We suspect our DNSMOS invocation is miscalibrated for AEC
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outputs β particularly near-silent clips, which are out of distribution
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for a speech-quality predictor β and would rather withhold the numbers
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than publish misleading ones.
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## Architecture
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| Component | Value |
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| Sample rate | 16 kHz |
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| Analysis basis | DCT-II (Conv1d filterbank, 512 filters, stride 256, frozen) |
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| Mic encoder | 5 blocks: 2 β 32 β 40 β 40 β 40 β 40 |
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| Kernel | (4, 4) time Γ freq, causal padding |
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| Parameters | ~0.9 M |
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##
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# LocalVQE β Local Voice Quality Enhancement
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Real-time joint acoustic echo cancellation (AEC), noise suppression (NS), and
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dereverberation for 16 kHz speech. A from-scratch derivative of **DeepVQE**
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(Indenbom et al., Interspeech 2023 β *DeepVQE: Real Time Deep Voice Quality
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Enhancement*, [arXiv:2306.03177](https://arxiv.org/abs/2306.03177)), redesigned
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for quantization-aware local CPU/GPU inference. The DCT-II analysis/synthesis
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(replacing STFT), S4D bottleneck, GGML streaming graph, and training pipeline
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are work of this project β no paper yet.
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**Authors:** Richard Palethorpe ([richiejp](https://github.com/richiejp)) and
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Claude (Anthropic).
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Project source: <https://github.com/richiejp/LocalVQE>
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## Files
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## Usage (GGML / C++ / Go)
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```bash
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# Build the ggml binary
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cd ggml && cmake -B build -DCMAKE_BUILD_TYPE=Release && cmake --build build -j
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# Run inference on a 16 kHz WAV pair
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./build/bin/localvqe localvqe-v1-f32.gguf \
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--in-wav mic.wav ref.wav --out-wav enhanced.wav
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```
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Per-frame wall time on Zen4 (24 threads): ~1.66 ms (9.6Γ realtime at
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16 kHz / 256-sample hop).
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## Architecture
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| Component | Value |
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|-----------|-------|
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| Sample rate | 16 kHz |
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| Analysis basis | DCT-II (Conv1d filterbank, 512 filters, stride 256, frozen) |
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| Mic encoder | 5 blocks: 2 β 32 β 40 β 40 β 40 β 40 |
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| Kernel | (4, 4) time Γ freq, causal padding |
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| Parameters | ~0.9 M |
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## Upstream citation (DeepVQE)
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```bibtex
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@inproceedings{indenbom2023deepvqe,
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title={{DeepVQE}: Real Time Deep Voice Quality Enhancement for Joint Acoustic
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Echo Cancellation, Noise Suppression and Dereverberation},
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author={Indenbom, Evgenii and Beltr{\'a}n, Nicolae-C{\u a}t{\u a}lin and
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Chernov, Mykola and Aichner, Robert},
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booktitle={Interspeech},
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year={2023},
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doi={10.21437/Interspeech.2023-2176}
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}
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```
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