pytorch-kaldi

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I'd like to train a model on reverberant speech using the alignments generated from the corresponding anechoic data. Currently, I'm doing something similar to TIMIT_joint_training_liGRU_fbank.cfg, where I am using the reverberant TIMIT recipe to extract the features and the anechoic recipe for lab_folder and lab_graph. I noticed that decode_dnn.sh uses the lab_graph to generate the lattice rather than the graph constructed from the reverberant acoustic model.

What is the easiest way to specify using the anechoic alignments and reverberant graph?

I just wanted to follow up an ask if anyone has suggestions.