Comments (1)
Yes, it generally works. You can reuse some IPA symbols from the ASR model (there are 178 tokens, many are not used) for these voice attributes. You can just finetune the pre-trained ASR models with your new phonemization rules (instead of re-training as you only star to use a few unused tokens).
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Related Issues (20)
- Strange Loss Behavior During Stage Two Training - Not Decreasing after Diff Epoch HOT 2
- Finetune on ljspeech or libritts? HOT 1
- Better LJSpeech or LibriTTS for finetuning a single speaker voice? Or training from scratch with not so much data? HOT 3
- SLM Adversarial Training did not start when finetuning HOT 11
- Second stage training with smaller window size HOT 1
- Possible Bug in Style Diffusion Inference Code
- Issue with impropper pauses and random bursts of noise
- Cannot Convert float NaN to integer HOT 1
- HELP WANTED!!!!!!!!!!! HOT 3
- asr negative loss
- Resuming finetuning uses second to last epoch
- Help Wanted For Stage-1 HOT 2
- Inference with multilingual PL-BERT Model HOT 4
- During training, the graphics memory has been continuously increasing
- May be a bug? input parameters for model.predictor_encoder and model.style_encoder in train_finetune.py
- S_loss = 0 ... why? HOT 2
- Inference Error: context_features exists but no features provided HOT 1
- Speech conditioning like tortoise TTS HOT 1
- FP8 Fine Tuning Crashes HOT 1
- Error Message After Using a fine tuned ASR Model
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