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pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
Thanks for this wonderful library, but it would be much more intuitive for users to get started by providing some simple but clearly training process on self-defined dataset.
The README.md file says to run the following command:
find /media/kaldi_models/ -type f | xargs sed -i 's:test:/opt:g'
The intent seems to be to change paths in ivector_extractor.conf and online_nnet2_decoding.conf from test/models/... to /opt/models/... where they will work with the docker image. However, that command also changes all instances of "test" in the wordlist words.txt! So for
I think the filenames in models.sh referred to on lines 4-9 should refer to kaldi-generic-en-tdnn_f-r20190609* which is downloaded on line 3.