Comments (2)
Hi !
For now, the only solution is to first train your pytorch model, and then call run_exp.py with a modified conf file with the number of epoch set to 0 (and also a specific [dataset] section that you can call as a testing dataset. We are aware that this is not optimal for real production case, and we are currently working on a side script that one can call to just decode .wav files from a previously trained pytorch model. Nonetheless, you can dive a bit on the run_exp.sh script to better understand how you can easily build your own script (if you are in a hurry).
I worked a bit with Kaldi in production environment (with automatic transcriptions of uploaded audio files). Nonetheless, and as you mention, the decoding time can be a problem. One of the solution we found is to use speaker diarization, so we can split the decoding in multiple threads with one thread equal to a speaker.
from pytorch-kaldi.
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Related Issues (20)
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