metadata
license: mit
library_name: onnxruntime
tags:
- voice-conversion
- onnx
- vconnx
- knn-vc
pipeline_tag: audio-to-audio
vconnx · kNN-VC (pure ONNX)
ONNX export of kNN-VC (Baas et al., Interspeech 2023, MIT) for the vconnx voice-conversion library: WavLM-Large layer-6 feature extractor + prematched HiFi-GAN vocoder; the kNN regression step is pure numpy at inference time. Any-to-any voice conversion at 16 kHz, CPU-only.
| file | role | size |
|---|---|---|
wavlm_layer6.onnx |
feature extractor (fp32) | 387 MB |
wavlm_layer6_q8.onnx |
feature extractor (int8) | 98 MB |
hifigan_knnvc.onnx |
vocoder (fp32) | 63 MB |
hifigan_knnvc_q8.onnx |
vocoder (int8) | 25 MB |
Export parity vs the torch reference (max abs): WavLM see report · HiFi-GAN see report (full reports in the repo).
Usage
from vconnx import VoiceCloner
out = VoiceCloner(engine="knnvc").clone_voice("source.wav", "reference.wav")
Provenance and upstream license: see PROVENANCE.md. Weights derive from
bshall/knn-vc (MIT) and
microsoft WavLM (MIT).