Full Parameter Finetuning Malaysian Emilia F5-TTS v2
Continue training from SWivid/F5-TTS on Malaysian-Emilia,
with total 8472 hours included 600 hours Mandarin sampled from amphion/Emilia-Dataset.
Features
- This model should be able to zero-shot voice conversion any Malaysian and Singaporean speakers.
- This model able to generate basic filler sounds such as
erm,huh, for example below,
Isu sekarangnya, erm, kita harus jadi yang terbaik untuk rakyat Malaysia, dan kita, uh, kena makan nasi lemak yang sedap lagi lazat, hah, penat nak kena cakap.
Checkpoints
We uploaded full checkpoints with optimizer states at checkpoints.
Dataset
We train on postfilter Malaysian-Emilia called Malaysian-Voice-Conversion
Source code
All source code at https://github.com/mesolitica/malaya-speech/tree/master/session/f5-tts
Inference Providers
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Model tree for mesolitica/Malaysian-F5-TTS-v2
Base model
SWivid/F5-TTS