Open kelvinqin opened 2 years ago
Hi @kelvinqin Thanks for your comment.
W2Layer is almoust combination of deepspeech2 and Wave2Letter models. Unlike deepspeech2, I added one RNN layer after VGG extraction block and one RNN block between the layers of the Wave2Letter model.
Dear Gheyret, Thanks so much for your reply, now I understood why I did not figure out its "source", it turns out that you are the source :-) Great work, and your work is great because the code is much clear than other "deeply wrapped" framework,
So W2Llayer means "Wave 2 Letter layer", is that correct please?
BTW, do you have plan to build a conformer system?
A small question --- in training, why you don't use encoder's output to calculate CTC_loss, instead, you use W2Llayer's output to calculate the CTC_loss? (See train.py, line 130) Not sure if it is a good idea to calculate it using "encoder_padded_outputs"?
Best regards, Kelvin
Dear Gheyret, Thanks for your work.
I spent some time today to try to figure out the source of this feature extraction layer, can you point me the paper/any reference on it?
I think it is a great design to extract speech features, so just want to understand it more deeply,
Thanks a lot,
Kelvin