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.
I'm running the TIMIT LSTM on custom features, and was able to successfully train a model. Now I'm testing the model using a custom test set, but I'm experiencing an issue where the test features do not get forwarded through the trained model. Here is the terminal output:
Additionally, the log file only indicates that hmm-info and ali-to-pdf were run, but there are no errors or warnings listed. I suspect this issue has to do with modifying the phonemap file, score.sh, and timit_norm_trans.pl to map to 41 phones rather than 40 phones. I reverted back to using 40 phones, but the features never appear to be forwarded and the code seems to be stuck at the decoding phase.
Do you have any suggestions on how to solve this issue?
I'm running the TIMIT LSTM on custom features, and was able to successfully train a model. Now I'm testing the model using a custom test set, but I'm experiencing an issue where the test features do not get forwarded through the trained model. Here is the terminal output:
Additionally, the log file only indicates that hmm-info and ali-to-pdf were run, but there are no errors or warnings listed. I suspect this issue has to do with modifying the phonemap file, score.sh, and timit_norm_trans.pl to map to 41 phones rather than 40 phones. I reverted back to using 40 phones, but the features never appear to be forwarded and the code seems to be stuck at the decoding phase.
Do you have any suggestions on how to solve this issue?