voiceclonnx — pure-ONNX voice conversion
Collection
ONNX exports powering the vconnx voice-conversion library: one repo per engine, with parity reports and provenance. • 10 items • Updated
vconnx-openvoice-v2
ONNX export of the OpenVoice v2 tone-color converter (myshell-ai/OpenVoice, MIT license) for use with vconnx — a pure-ONNX zero-shot voice conversion toolkit.
Export details
Both components are exported from the upstream SynthesizerTrn
(myshell-ai/OpenVoice) with strict state-dict loading — no architecture
reconstruction. The checkpoint loads with 0 missing keys and 0 unexpected keys.
| Component | File | Size |
|---|---|---|
| Reference encoder (FP32) | tone_ref_encoder.onnx |
3.1 MB |
| Reference encoder (INT8) | tone_ref_encoder_q8.onnx |
2.2 MB |
| Voice converter (FP32) | tone_converter.onnx |
122.1 MB |
| Voice converter (INT8) | tone_converter_q8.onnx |
38.9 MB |
Architecture
| Sub-graph | ONNX inputs | ONNX output |
|---|---|---|
tone_ref_encoder.onnx |
spec (B, T, 513) float32 — linear STFT magnitude |
tone_embedding (B, 256) |
tone_converter.onnx |
spec (B, 513, T), spec_lengths (B,), src_g (B, 256, 1), tgt_g (B, 256, 1) |
audio (B, 1, samples) float32 — raw waveform |
The converter includes the full VITS-style flow decoder and HiFi-GAN vocoder; it outputs raw audio directly. No separate vocoder step is needed at inference.
Preprocessing: linear magnitude spectrogram matching upstream
spectrogram_torch — Hann window, n_fft=1024, hop=256, win=1024, reflect-pad
384 on each side, sqrt(Re² + Im² + 1e-6). No log compression.
Parity (upstream torch vs ONNX)
| Component | max_abs_delta | mean_abs_delta | Status |
|---|---|---|---|
tone_ref_encoder |
8.64e-07 | 2.45e-07 | PASS |
tone_converter (5 seeds) |
1.08e-02 (worst) | 1.26e-04 (avg) | PASS |
The converter max_abs divergence is due to float32 accumulation through 4
residual coupling blocks in the flow — the quality-relevant metric is
mean_abs, which passes at 1e-3.
E2E sanity check
Converted a 2 s synthetic source (220 Hz harmonics) to a 330 Hz reference:
| Metric | Value |
|---|---|
| Output duration | 1.997 s (source 2.000 s, ratio 0.998) |
| RMS | 0.268 |
| Spectral flatness | 0.072 (tonal, not noise) |
| Sample rate | 22050 Hz |
Usage
from vconnx import VoiceCloner
cloner = VoiceCloner(engine="openvoice")
cloner.clone_voice("source.wav", "reference.wav", "output.wav")
Or with the low-level adapter:
from vconnx.engines.openvoice import OpenVoiceV2Adapter
adapter = OpenVoiceV2Adapter(quantized=False)
adapter.clone_voice("source.wav", "reference.wav", "output.wav")
Install with: pip install vconnx[openvoice]
Provenance
- Upstream weights: myshell-ai/OpenVoiceV2
- Upstream source: myshell-ai/OpenVoice
- License: MIT ("Starting from April 2024, both V2 and V1 are released under MIT License. Free for commercial use." — official README)
- Export method: legacy TorchScript ONNX exporter (
dynamo=False), opset 14 (new dynamo exporter fails on GRU) - Strict load: 0 missing keys, 0 unexpected keys
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