Hello, I noticed a few stale branches where things have been tried, such as batch normalization, dilated convolutions, or filter banks instead of mfcc. I’m curious - what was the impact of those features? If there were improvements, why haven’t those features made it into the main branch?
Also, why are you using DeepSpeech1 architecture, and not DeepSpeech2?
Finally, was the 6.5% accuracy on LibriSpeech achieved with the architecture as is currently specified in master branch (that is, DS1 model using LSTM cells)?