cmds2/run_FeatExt_Kaldi.py  --  Extract Features from a Trained Model and Save Features to the Kaldi Format ---------------------------------------------------------------------------------------------------------------------- Arguments argument meaning default value --in-scp-file              path to the .scp file for network input features required                     --out-ark-file path to the (Kaldi-formatted) .ark file to store the network activation required --nnet-param path to model parameters required --nnet-cfg path to model config required --layer-index     the index of the layer from which features are generated. Layers are 0-based indexed, starting from the first hidden layer. Set it to "-1" when you want to do classification. That is, we extract features from the final softmax layer. required Example python cmds2/run_FeatExt_Kaldi.py --in-scp-file input.1.scp \                                   --out-ark-file feats.1.ark \                                   --nnet-param cnn.param --nnet-cfg cnn.cfg \                                   --layer-index 1