Seed-VC

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Currently released model supports zero-shot voice conversion 🔊 and zero-shot singing voice conversion 🎙. Without any training, it is able to clone a voice given a reference speech of 1~30 seconds.

To find a list of demos and comparisons with previous voice conversion models, please visit our demo page🌐

We are keeping on improving the model quality and adding more features.

Evaluation📊

We have performed a series of objective evaluations on our Seed-VC's voice conversion capabilities. For ease for reproduction, source audios are 100 random utterances from LibriTTS-test-clean, and reference audios are 12 randomly picked in-the-wild voices with unique characteristics.

Source audios can be found under ./examples/libritts-test-clean
Reference audios can be found under ./examples/reference

We evaluate the conversion results in terms of speaker embedding cosine similarity (SECS), word error rate (WER) and character error rate (CER) and compared our results with two strong open sourced baselines, namely OpenVoice and CosyVoice.
Results in the table below shows that our Seed-VC model significantly outperforms the baseline models in both intelligibility and speaker similarity.

Models\Metrics	SECS↑	WER↓	CER↓
OpenVoice	0.7547	0.1546	0.0473
CosyVoice	0.8440	0.1898	0.0729
Seed-VC(Ours)	0.8676	0.1199	0.0292

ASR result computed by facebook/hubert-large-ls960-ft model
Speaker embedding computed by resemblyzer model

You can reproduce the evaluation by running eval.py script.

python eval.py --source ./examples/libritts-test-clean \
--reference ./examples/reference
--output ./examples/eval/converted/
--diffusion-steps 25
--length-adjust 1.0
--inference-cfg-rate 0.7
--xvector-extractor "resemblyzer"
--baseline ""  # fill in openvoice or cosyvoice to compute baseline result
--max-samples 100  # max source utterances to go through

Before that, make sure you have openvoice and cosyvoice repo correctly installed on ../OpenVoice/ and ../CosyVoice/ if you would like to run baseline evaluation.

Installation📥

Suggested python 3.10 on Windows or Linux.

pip install -r requirements.txt

Usage🛠️

Checkpoints of the latest model release will be downloaded automatically when first run inference.

Command line inference:

python inference.py --source <source-wav> \
--target <referene-wav>
--output <output-dir>
--diffusion-steps 25 # recommended 50~100 for singingvoice conversion
--length-adjust 1.0
--inference-cfg-rate 0.7
--f0-condition False # set to True for singing voice conversion
--auto-f0-condition False # set to True to auto adjust source pitch to target pitch level, normally not used in singing voice conversion
--semi-tone-shift 0 # pitch shift in semitones for singing voice conversion

where:

source is the path to the speech file to convert to reference voice
target is the path to the speech file as voice reference
output is the path to the output directory
diffusion-steps is the number of diffusion steps to use, default is 25, use 50-100 for best quality, use 4-10 for fastest inference
length-adjust is the length adjustment factor, default is 1.0, set <1.0 for speed-up speech, >1.0 for slow-down speech
inference-cfg-rate has subtle difference in the output, default is 0.7
f0-condition is the flag to condition the pitch of the output to the pitch of the source audio, default is False, set to True for singing voice conversion
auto-f0-condition is the flag to auto adjust source pitch to target pitch level, default is False, normally not used in singing voice conversion
semi-tone-shift is the pitch shift in semitones for singing voice conversion, default is 0

Gradio web interface:

python app.py

Then open the browser and go to http://localhost:7860/ to use the web interface.

TODO📝

CHANGELOGS🗒️

2024-09-26:
- Added objective evaluation results
- Changed speech content encoder to OpenAI Whisper
2024-09-22:
- Updated singing voice conversion model to use BigVGAN from NVIDIA, providing large improvement to high-pitched singing voices
- Support chunking and streaming output for long audio files in Web UI
2024-09-18:
- Updated f0 conditioned model for singing voice conversion
2024-09-14:
- Updated v0.2 pretrained model, with smaller size and less diffusion steps to achieve same quality, and additional ability to control prosody preservation
- Added command line inference script
- Added installation and usage instructions