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text embedding dimension
See original GitHub issueHi. Since I tried to train Glow-TTS using Mandarin datasets, there are about 300 symbols in symbols.py. Therefore, it seems that I need to increase the text embedding depth. I notice that in your paper, you mentioned that:
Does the Embedding Dimension here stands for “text embedding dimension”?
If it is, which parameter here should I modify, hidden_channels , or hidden_channels_enc?
Thank you very much!
Issue Analytics
- State:
- Created 3 years ago
- Comments:6
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Hi, you can try the trick add blank token between any two input tokens. My experiment in Chinese shows that this trick can improve pronunciation significantly.
由于涉及到数据安全问题，我没法给你提供demo，见谅。目前我的结论是：对于播报式的音库，可以正常地合成，对于表现力很丰富的音库，合成会出问题。