New LJSpeech model

[erogol]

Some of the improvements are as follows

• History queue to be used as an auto-regressive connection. It enables you to train the model by changing the prediction frame size by only fine-tuning the output layer of the network without any architectural change. It is also a solution for prenet dropout #50

• Embedding layers to initialize decoder hidden states.

• Phoneme-based training for faster convergence and robust results.

• Model prediction frame size is 2 (r=2), leading to better voice synthesis and spectrogram reconstruction. It's a better candidate to cooperate with a neural vocoder.

• No explicit weighting for lower frequency part of the spectrograms.

• This model is trained with r=5 for 120K iterations and then continued to train until 185K iterations.

This model is a checkpoint from 185K iteration. It might reach better results through longer training.