I'm using a Hidden Markov Model in order to train an application for gesture recognition.

Currently, I have gathered samples, and, using a library have trained these values (They have been passed through a Baum–Welch function in order to train the dataset.

I then (in real-time) have computed the gestures of each model, however, I get the wrong result back. I have only ever used a HMM and trained using MFCC features.

Does the actual input data have to be passed through the Baum-Welsh function too, in order to compute the Viterbi-Decoder algorithm? When using MFCC, I did not have to perform such an operation, but, I was lead to believe that the HMM can be trained using the MFCC features, in this instance the real-data is just of doubles.


Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.