I wish to use a different feature set, STE (Short Term Energy). After an .ark file with these features, I could use traditional Kaldi way of training GMM-HMM. (STE is used for EEG, not for speech here)
I wish to first decode the raw_mfcc_train.1.ark, replace the frame level features, and finally encode the same way. I understand that ark file is archive holding all key-value pairs. keys being utterance IDs and values being features per frame.
1. What encoding is used?
2. How do I decode it using python's simple with open() function maybe in 'rb' mode?