Krogee VC — Seed-VC fine-tuned for "Zephyr"
A fine-tuned Seed-VC voice-conversion
model that converts any spoken audio into the voice of the speaker Zephyr.
It is cross-lingual - the source speech does not need to be Twi. It uses the
seed-uvit-whisper-small-wavenet
architecture (22.05 kHz, Whisper-small content encoder, BigVGAN vocoder).
The target voice was fine-tuned on clean Twi (Akan) utterances from
ghananlpcommunity/ghana-twi-synthesized-speech.
Try the demo
Convert a clip straight in your browser:
The demo includes a few bundled example clips (Twi, Ga, Ewe, Swahili, Yoruba) so you can hear the cross-lingual conversion immediately.
Files
| File | Description |
|---|---|
ft_model.pth | Fine-tuned checkpoint (DIT + BigVGAN) |
config_dit_mel_seed_uvit_whisper_small_wavenet.yml | Model/training config |
ref_zephyr.wav | Reference utterance of the speaker used for conversion |
LICENSE | GPL-3.0 (upstream of seed-vc) |
README.md | This file |
Usage
Use the checkpoint directly with Seed-VC inference:
python inference.py \
--source <your-speech.wav> \
--target ref_zephyr.wav \
--output out/ \
--diffusion-steps 25 \
--length-adjust 1.0 \
--inference-cfg-rate 0.7 \
--checkpoint ft_model.pth \
--config config_dit_mel_seed_uvit_whisper_small_wavenet.yml
Training summary
- Dataset:
ghananlpcommunity/ghana-twi-synthesized-speech(Twi, speaker Zephyr), ~10.5k valid clips - Steps: 2500, batch size 2, saved every 1250 steps
- Baseline:
seed-uvit-whisper-small-wavenet(zero-shot)
License
This is a derived work of
Seed-VC (GPL-3.0), verbatim in
LICENSE. The training data is the publicly released
ghananlpcommunity/ghana-twi-synthesized-speech dataset (see its own terms);
extra pretrained weights (CAM++ / OpenVoice) are auto-downloaded by the
inference stack under their respective licenses.