Hello. Thanks for your great work! I'm new to the TTS area and this notebook could be a good start.
However, I gave it a try and found out the Chinese model at present doesn't make pauses. I wonder has this been one of your potential improvements yet?

cc: @azraelkuan (person in charge)

@wyp1996 for now, we do not have a frontend model, but we have place #1,2,3,sil in the training

@dathudeptrai Does it already in master branch for support?

@jinfagang everything is on master branch. (updated content :D.)

@dathudeptrai Any readme on how to train on Biaobei data?

@jinfagang jsut download biaobei data and extract it to baker

tensorflow-tts-preprocess --dataset baker --rootdir ~/Data/baker --outdir dump --config ./preprocess/baker_preprocess.yaml

and train it using baker's yaml.

@azraelkuan As I know the sampling rate of the audio in the Biaobei dataset is 48k, but in the baker_preprocess.yaml the sampling rate is set as 24k. I didn't try the preprocess. Is that a mistake or I misunderstand the code?

@IreneZhou2018 the sampling rate in config is target sampling rate, if the dataset's sample rate is 48k so we re-sample it (see code here https://github.com/TensorSpeech/TensorFlowTTS/blob/master/tensorflow_tts/bin/preprocess.py#L194-L196)

@dathudeptrai ok, thanks for your reply and the work is amazing!

TensorFlowTTS Serving：
https://github.com/MachineLP/QDServing/tree/master/model_serving
https://github.com/MachineLP/QDServing

TensorflowTTS训练数据生成：拉取文本数据、将文本专为拼音、基于阿里云TTS生成TensorflowTTS训练音频、训练前的preprocess/normalize：https://github.com/MachineLP/TensorFlowTTS_chinese/tree/master/generate_tts_data

TensorflowTTS训练数据生成：拉取文本数据、将文本专为拼音、基于阿里云TTS生成TensorflowTTS训练音频、训练前的preprocess/normalize：https://github.com/MachineLP/TensorFlowTTS_chinese/tree/master/generate_tts_data

Hi, do you have a more specific Readme? It seems promising and I'd like to have to try :)

@jinfagang jsut download biaobei data and extract it to baker

tensorflow-tts-preprocess --dataset baker --rootdir ~/Data/baker --outdir dump --config ./preprocess/baker_preprocess.yaml

and train it using baker's yaml.

it seems that fastspeech2 model do not work properly when sentence is long ? like 君不见 黄河之水天上来 奔流到海不复回 君不见 高堂明镜悲白发 朝如青丝暮成雪 人生得意须尽欢 莫使金樽空对月

it seems that fastspeech2 model do not work properly when sentence is long ? like 君不见 黄河之水天上来 奔流到海不复回 君不见 高堂明镜悲白发 朝如青丝暮成雪 人生得意须尽欢 莫使金樽空对月

#208 (comment)

Thank you . I am still evaluating the model .

Chinese TTS欢迎加微信:lp9628，进入微信群讨论训练测试细节问题。

@dathudeptrai I try to train get this error:

2020-10-16 22:28:20.499294: W tensorflow/core/grappler/optimizers/loop_optimizer.cc:906] Skipping loop optimization for Merge node with control input: cond/branch_executed/_8
Traceback (most recent call last):
  File "examples/tacotron2/train_tacotron2.py", line 488, in <module>
    main()
  File "examples/tacotron2/train_tacotron2.py", line 476, in main
    trainer.fit(
  File "/media/jintian/samsung/source/ai/swarm/exp/TensorFlowTTS/tensorflow_tts/trainers/base_trainer.py", line 870, in fit
    self.run()
  File "/media/jintian/samsung/source/ai/swarm/exp/TensorFlowTTS/tensorflow_tts/trainers/base_trainer.py", line 101, in run
    self._train_epoch()
  File "/media/jintian/samsung/source/ai/swarm/exp/TensorFlowTTS/tensorflow_tts/trainers/base_trainer.py", line 123, in _train_epoch
    self._train_step(batch)
  File "examples/tacotron2/train_tacotron2.py", line 109, in _train_step
    self.one_step_forward(batch)
  File "/home/jintian/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 780, in __call__
    result = self._call(*args, **kwds)
  File "/home/jintian/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py", line 840, in _call
    return self._stateless_fn(*args, **kwds)
  File "/home/jintian/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 2829, in __call__
    return graph_function._filtered_call(args, kwargs)  # pylint: disable=protected-access
  File "/home/jintian/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 1843, in _filtered_call
    return self._call_flat(
  File "/home/jintian/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 1923, in _call_flat
    return self._build_call_outputs(self._inference_function.call(
  File "/home/jintian/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/function.py", line 545, in call
    outputs = execute.execute(
  File "/home/jintian/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/execute.py", line 59, in quick_execute
    tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,
tensorflow.python.framework.errors_impl.InvalidArgumentError:    Trying to access element 62 in a list with 62 elements.
	 [[{{node while_19/body/_1/while/TensorArrayV2Read_1/TensorListGetItem}}]]
	 [[tacotron2/encoder/bilstm/forward_lstm/PartitionedCall]] [Op:__inference__one_step_forward_23575]

Function call stack:
_one_step_forward -> _one_step_forward -> _one_step_forward

My command:

python examples/tacotron2/train_tacotron2.py \                                                                                                               ⎇  master ✘ !?|73cac7f
  --train-dir ./dump/train/ \
  --dev-dir ./dump/valid/ \
  --outdir ./examples/tacotron2/exp/train.tacotron2.baker.v1/ \
  --config ./examples/tacotron2/conf/tacotron2.baker.v1.yaml \
  --use-norm 1 \
  --mixed_precision 0 \
  --resume ""

1. The punctuation pause does not seem to be handled.
2. Arabic numbers cannot be directly predicted.
3. Hope this can be mixed in Chinese and English.

Chinese TTS now available, thank @azraelkuan for his support :D. The model used Baker dataset here (https://www.data-baker.com/open_source.htmlt). The pretrained model licensed under CC BY-NC-SA 4.0 (https://creativecommons.org/licenses/by-nc-sa/4.0/) since the dataset is non-commercial :D

Pls check out the colab bellow and enjoy :D.

https://colab.research.google.com/drive/1YpSHRBRPBI7cnTkQn1UcVTWEQVbsUm1S?usp=sharing

Note: this is just init results, there are more things can be done to make the model better.

cc: @candlewill @l4zyf9x @machineko

@jinfagang everything is on master branch. (updated content :D.)

hello, the link to baker dataset was expired , and the officical website show that have no right to access the dataset , i hate to say that ,but can you provide annother way to get the dataset?

@jucaowei The link is here. The data only has a female voice.

@jucaowei The link is here. The data only has a female voice.

thank you !!

@jucaowei The link is here. The data only has a female voice.

404 error ,you can acess the website ? i got 404 not found
HTTP Status 404 – Not Found
Type Status Report
Message /open_source.htmlt
Description The origin server did not find a current representation for the target resource or is not willing to disclose that one exists.

@jucaowei
I can access the website normally. Which country are you in now? Maybe a VPN is needed for network problems?

@jucaowei
I can access the website normally. Which country are you in now? Maybe a VPN is needed for network problems?

i already use VPN with HK node,not working, but my friend access the website right now, really appreciate for you reply

@azraelkuan Hi! Thanks for your work. Compared with some other reproduction projects, your reproduced tacotron2 can synthesize very long sentences without stress or omission.
I have tried your job to achieve a maximum of about 90 seconds. To be reasonable, the Biaobei dataset is relatively short sentences, and the model trained with Biaobei should not be able to synthesize such long sentences.
Have you done any special treatment of long sentences?