[mlpack-git] [mlpack] HMM for sign language recognition (#493)

[kahrabji08]

Hi there

Am trying to use **mlpack** for my MSc research in sign language recognition I know the theory of **HMM** and I tested the command line programs provided for HMM by mlpack I am using **cyberGloves**(which provides 23 values) and a **tracker**(which provides 6 values for position and orientation)  for the data collectionSo my **feature vector is of width 29** I am just not sure about few things for which I hope to get your help:

1 **number of models**: Am doing continuous recognition so I got my data by recording 40 sentences coming from 80 words I think I have to build an HMM model for **each word**, this means 80 models, **Am I right**? 

2 **Training Data** : to prepare the training data i should put all the training examples of one word in one data file and use it for training **For example** if the first recorded sentence is " I LOVE FOOTBALL" and the 2nd sentence was " I LOVE MY MOTHER" then I should take the sensor data correspond to the word "LOVE" from the first sentence and put it in a new file, then add to that file the sensor data correspond to same word "LOVE" from the second sentence and so on for the 40 sentences And then Start training Am I right?

3 What should be the type of my HMM gaussian or gmm? if it's the later how could I know the number of gaussians in each GMM?

4 How should I label the data? and How to choose the number of States?

5 **Recognition**: I want to perform sentence recognition So in order to do that, for **each feature vector** should I first find the most probable model using `hmm_loglik` then use `hmm_viterbi` based on that model to find the hidden state(the word)?

Thanks for your help and support,
Mohamed






 

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https://github.com/mlpack/mlpack/issues/493
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