The question of model

[AnnaWang288]

Hi, thank you for sharing your code.I am using your code for my further research recently. And now I have a question in the process of practice. I am appreciation it if get your answer.
In the model training of the Code file, you used the Gaussian mixture model. But in the model training of the nnCode, svmCode, and hmmCode files, you used the Gaussian HMM. Why should it be set like this？

[SuperKogito]

Hi,
I am sorry if the repository structure is a bit confusing. This is actually related to the way this repository evolved with time. I have been planning to make an update to clear things up, but I kept delaying it. Hopefully by Sunday, I will update to the repository and clear things up. For now here a quick explanation of the structure:

• Code repository: is the original code for voice based gender recognition using Gaussian mixture models.
• hmmCode repository: is the code for voice based gender recognition using hidden Markov models.
• svmCode repository: is the code for voice based gender recognition using Support vector machines.
• nnCode repository: is the code for voice based gender recognition using a basic neural network.

All the codes are very similar in structure and concept except for the model and its required data formatting.

[AnnaWang288]

I'm very glad for your reply. I am pleasure to get your explanation why you still use Gaussian model before using svm classifier, and why choose Gaussian HMM model instead of Gaussian mixture model or something else.
Looking forward to hearing from you.Thank you:)

[SuperKogito]

I get your confusion, the code is not clean enough and I am working on it.
In the hmmCode, if you look closely you will notice that I am only using the same variable names but in one example I am using the HMMs and the other GMMs.

The only places where I mix GMMs with another model are in the NN (Neural Network) and the SVM (Support Vector Machines) code; In these 2 examples I used the means of the Gaussian Mixture Models as the input features for the NN or the SVM.