naveenss1995

Yes the above comment helps, Yes the model mentioned above also works, issue arises when you do tranfer learning on top of that model.

Its resolved modified audio parsing method in latest SpectrogramParser to use load_audio_from_txt, issue was resolved.

The fix worked 99 % of the time but unfortunatey its giving File "/home/ubuntu/ds/live.ds.pytorch.v2/deepspeech.pytorch/deepspeech_pytorch/loader/data_loader.py", line 19, in load_audio_from_txt sound = sound.astype('float32') / 32767 # normalize audio ValueError: could not convert...

By latest SpectroGram Parser i mean the latest code in SeanNaren/deepspeech.pytorch. Yes as you mentioned above the error happens when i am stopping the recording. If this is expected behaviour...

I am getting same issue. ( Continuation Frames ) . Note i am using it without lzstring compression (so my byte array sizes are prety huge). Did you find any...