Is there a Jupyter tutorial notebook for BERT ASR postprocessing?
Actually never mind, I can just train using other text-to-text notebooks as a new language pair, the pair being ASR output to ground truth. Hey, they've explained in other issues - https://github.com/NVIDIA/NeMo/issues/1156, https://github.com/NVIDIA/NeMo/issues/1126 that it hasn't been ported yet, but looks like they have some workarounds to adding a Language Model for incorporating context. They might want to consider adding it to their docs since it seems to pop up often.



> Actually never mind, I can just train using other text-to-text notebooks as a new language pair, the pair being ASR output to ground truth.

Also, would you mind elaborating a bit on your process? Did it help with results in your case? Hi @ShantanuNair, they had this script in older releases, they just deleted it without explanation.

I will elaborate, with this caveat: It didn't help.

The method was just to take the predicted output from my NeMO Quartz15x15 trained ASR net, pair it with the gold translation, and train a new net.  The new net was this Seq2Seq model from Ben Trevett: https://github.com/bentrevett/pytorch-seq2seq/blob/master/6%20-%20Attention%20is%20All%20You%20Need.ipynb

I suppose I could have done the equivalent  model in NeMo but they [deleted the example](https://github.com/NVIDIA/NeMo/tree/fa68d336cfefbbbb1849ff1b6ef454149f45234d/examples/nlp/asr_postprocessor).    For the NIST exercise I was doing, I needed to train from scratch, and the (deleted) example only showed starting from a pretrained model.  I already knew the Ben Trevett code so I went with that.

The score after adding this "afterburner" net trained on the mistakes of the ASR net was only negligeably higher than without it. 
BERT ASR postprocessing is described here: https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/v0.10.1/nlp/asr-improvement.html

Is there a notebook in the GitHub to demo this in combination with transfer learning of QuartzNet15x5 for a new language?

It would be very helpful to show how to transfer-learn the Bert for a transfer-learned new language QuartzNet.

Also...what happened to all the files referenced in the docs, for example `examples/nlp/asr_postprocessor`

After some digging, I found them buried in an old version.  I hope this doesn't mean this doesn't work any more:

https://github.com/NVIDIA/NeMo/tree/fa68d336cfefbbbb1849ff1b6ef454149f45234d/examples/nlp/asr_postprocessor