aufklarer / Sidon-CoreML

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Total runs: 1.7K
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7-day runs: -195
30-day runs: -302
Model's Last Updated: August 30 2026
audio-to-audio

Introduction of Sidon-CoreML

Model Details of Sidon-CoreML

Sidon — Core ML (speech restoration / dereverberation)

On-device speech restoration (denoise + dereverberation + bandwidth restoration) for Apple Silicon, exported to Core ML (runs on the Neural Engine). Turns a noisy/reverberant clip into studio-quality 48 kHz speech — ideal for cleaning a voice-cloning reference before TTS, since it preserves speaker identity.

Two-stage pipeline:

16 kHz audio → [w2v-BERT log-mel front-end] → predictor (w2v-BERT 2.0, 8 layers)
            → cleansed features [1, T, 1024] → DAC decoder → 48 kHz audio
Variants
variant predictor vocoder bundle size peak RAM RTF (ANE)
fp16 FP16 FP16 713 MB 1711 MB ~120×
int8 INT8 (k-means palettized) FP16 407 MB 1321 MB ~110×

Total 246 M params (predictor 193.6 M + DAC vocoder 52.4 M). Output sample rate 48 kHz. int8 keeps the vocoder at FP16 (audio quality); only the predictor is palettized.

Files
path description
fp16/Sidon-Predictor.mlpackage w2v-BERT 2.0 (8L) + merged LoRA → features (FP16)
fp16/Sidon-Vocoder.mlpackage DAC decoder → 48 kHz audio (FP16)
int8/Sidon-Predictor.mlpackage predictor, 8-bit palettized
int8/Sidon-Vocoder.mlpackage DAC decoder (FP16)
Quality (no-reference MOS, 10 s clip)

DNSMOS P.835 (SIG/BAK/OVRL, higher = better) and UTMOS (naturalness, 1–5):

audio SIG BAK OVRL UTMOS speaker cos
input (reverberant) 3.46 3.40 2.90 2.99
fp16 3.53 4.09 3.28 3.32 0.797
int8 3.54 4.11 3.29 3.23 0.796

Restoration lifts OVRL 2.90 → 3.29 (driven by BAK 3.40 → 4.11 — reverb removed). Quantization is near-lossless on DNSMOS and speaker similarity; UTMOS shows a small naturalness cost (fp16 −0.09, int8 −0.17). Numbers are a single clip — average over a set for a definitive figure.

Front-end

The graphs take input_features [1, T, 160] from the w2v-BERT 2.0 SeamlessM4T feature extractor (16 kHz input). The sequence length is fixed (T = 499 ≈ 10 s) — chunk longer audio in the runtime. The front-end and chunking are handled by speech-swift .

Usage

Use via the speech-swift Apple SDK, e.g.:

speech enhance noisy-reference.wav -o clean.wav   # restore / dereverb on-device
// See speech-swift for the full API (loads the predictor + vocoder, runs the
// log-mel front-end, chunks, and writes 48 kHz audio).
Source

Exported from Sidon (sarulab-speech), checkpoint sidon-v0.1 ; paper arXiv:2509.17052 . Base SSL encoder: facebook/w2v-bert-2.0 ; vocoder: DAC (descript-audio-codec). All components are MIT-licensed.

Links

Runs of aufklarer Sidon-CoreML on huggingface.co

1.7K
Total runs
4
24-hour runs
-6
3-day runs
-195
7-day runs
-302
30-day runs

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Sidon-CoreML huggingface.co

Sidon-CoreML huggingface.co is an AI model on huggingface.co that provides Sidon-CoreML's model effect (), which can be used instantly with this aufklarer Sidon-CoreML model. huggingface.co supports a free trial of the Sidon-CoreML model, and also provides paid use of the Sidon-CoreML. Support call Sidon-CoreML model through api, including Node.js, Python, http.

aufklarer Sidon-CoreML online free

Sidon-CoreML huggingface.co is an online trial and call api platform, which integrates Sidon-CoreML's modeling effects, including api services, and provides a free online trial of Sidon-CoreML, you can try Sidon-CoreML online for free by clicking the link below.

aufklarer Sidon-CoreML online free url in huggingface.co:

https://huggingface.co/aufklarer/Sidon-CoreML

Sidon-CoreML install

Sidon-CoreML is an open source model from GitHub that offers a free installation service, and any user can find Sidon-CoreML on GitHub to install. At the same time, huggingface.co provides the effect of Sidon-CoreML install, users can directly use Sidon-CoreML installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

Sidon-CoreML install url in huggingface.co:

https://huggingface.co/aufklarer/Sidon-CoreML

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