Tacotron: Train TWEB dataset

[erogol]

Dataset: https://www.kaggle.com/bryanpark/the-world-english-bible-speech-dataset

[erogol]

Using the master branch had very poor performance due to the very long sequence length of the dataset. To alleviate the problem I try to use Truncated Backpropagation Through Time.

[erogol]

Dataset has a interesting frequency distribution, seems like post-processed after the recording.

[erogol]

This dataset is in very low quality. It is low-pass filtered applied. It causes low stop-token prediction and pronunciation errors, especially for novel words. Training with phonemes might improve the results.

Also I replaces ReLU with RReLU and removed Dropout in prenet. These changes improved the results but yet to be tested on other datasets.

Sound example: https://soundcloud.com/user-565970875/tweb-example-108k-iters-2810d57
Model : https://drive.google.com/open?id=1deQ2akq9cuyreda0DgZOiBdydkbgseWP

[erogol]

As I just discover, I trained the model with thw sampling rate 22050 which is default for LJSpeech but TWEB has 12000 sampling rate. That might be a important bug.

[viveknad94]

@erogol Is there any pretrained TTS model that has been trained with a male voice? I have been trying synthesize audio with the pretrained model (Tacotron-iter-108K on the TWEB dataset) but the commit is no longer present (2810d57). I get this error error: pathspec '2810d57' did not match any file(s) known to git.