Comments (3)
yqzhishen
commented on July 30, 2024
This seems like a possible labeling issue. If you didn't label the AP and SP areas accurately, the model may pronounce something on these two phonemes.
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loct824
commented on July 30, 2024
Do you mean that it relates to the quality of the transcriptions.csv? whether each labelled phoneme correctly correspond to the part in the audio? Any guidance how we could improve other than manually refine the phoneme time positions labelling? thanks.
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yqzhishen
commented on July 30, 2024
If you enabled some variance parameters then controlling them can be a workaround. But on the training side I cannot provide more advice without further information.
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Related Issues (20)
- Torch2.2 Error Variance HOT 5
- Support tension and voicing
- TypeError running variance inference (previously working) HOT 1
- ONNX inference 'depth' parameter HOT 6
- onnx exports to incorrect folder HOT 1
- Inference from OpenUTAU USTx -> DiffSinger DS not Carrying Over Parameters HOT 1
- AttributeError on ReFlow HOT 1
- Tracking: development around Rectified Flow HOT 3
- Export Acoustic Model Error:"size mismatch for fs2.txt_embed.weight" HOT 1
- Custom Trained DiffSinger Render Failed HOT 1
- 是否可以更改模型架构或者其他方式提升合成音质？ HOT 6
- Is removing background noise from audio beneficial to the quality of DiffSinger? HOT 2
- Question regarding pitch models (Reflow vs DDPM) HOT 3
- 关于唱法模型数据集 HOT 1
- Effects of transitioning mel_base from '10' to 'e' HOT 2
- In automatic optimization, `training_step` must return a Tensor, a dict, or None (where the step will be skipped). HOT 6
- ONNX Inference Scripts Documentation HOT 5
- Error training variance model HOT 3
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