Succeed to train THCHS30 in Chinese mandarin!

Hi all. I have good news that I have succeeded to train THCHS30 in Chinese mandarin. The code is open on my repo with just a little modification against the master branch. In this repo I used pinyin phoneme as symbols and the evaluation input are also sentences in Chinese pinyin. Since the number of Chinese characters are enormous, we can use pypinyin to translate into finite English symbols plus number 12345 as tone of voice. It produces good effect in 90K steps. The evaluation audio are here: eval_audio_92k.zip And the pre-trained model is here. And the align graph seems to be very good. However, the dataset THCHS30 is with multi-speakers so that there are some problems in some evaluation by chance like silence. So I still need to find some better mandarin dataset with single speaker and long hours enough for training. In all, this tacotron project is very good for me, thanks a lot.

[konghuanhuan]

@zhuyiif 问题解决了吗？

这个branch 我跑不起来，能帮忙看看是什么原因吗？ NotFoundError (see above for traceback): Restoring from checkpoint failed. This is most likely due to a Variable name or other graph key that is missing from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:

Key model/inference/decoder/Location_Sensitive_Attention/attention_bias not found in checkpoint [[{{node save/RestoreV2}} = RestoreV2[dtypes=[DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, …, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT], _device=“/job:localhost/replica:0/task:0/device:CPU:0”](_arg_save/Const_0_0, save/RestoreV2/tensor_names, save/RestoreV2/shape_and_slices)]]

[begeekmyfriend]

Hi all, I am sorry maybe I was wrong. The modification of hyper parameters such as mel fbank does not help improve but impair the result of evaluation. Therefore I have changed it back into 80. Apologize for my mistakes. See my latest commit https://github.com/begeekmyfriend/tacotron/commit/cbc2b877e2674a1271ab226d03ba3de64f69a65e