SVM-GMM

[Sara-Sa-Uk]

Hello Mr.Ayoub,
Thank you for your great work.

I got some issues while running the SVM-code could you help me please.

I have one question regarding the SVM-code, why we are training the data on .hmm.

And why we you used this?

Thank you in advance.

[SuperKogito]

Hello,
For your first question: as the trace-back shows, the problem seems to be a permission error, therefore try to run the code as an admin aka using sudo. Also make sure that you have installed ffmpeg.
As for the second question: the silence elimination part is needed so that the models are trained only on speech data and not speech+silence data. Eliminating the silence should help speed the system and improve its precision.

[Sara-Sa-Uk]

Thank you for your help, sorry I have one more question regarding SVM-Super vectors it's based on GMM-UBM right? dose it based on HMM, why we are saving the models as .hmm not .gmm?
Thank you again.

[SuperKogito]

you are welcome @Sara-Sa-Uk . You don't have to thank me in every message, this is a place to share knowledge so I am here to help and learn too.
As for your questions:

1. No, this is not a GMM-UBM system, I am only using GMMs because I only have two models to compare, so it should be enough. A GMM-UBM could be more accurate but I cannot compute UBMs using scikit-learn as this would result in a memory problem, so if you want to do that I suggest using bob.
2. It depends which code you are using, the code includes two different codes one for Gaussian mixture models (.gmm) and Hidden Markov models (.hmm). You can refer to this for more informations.

[Sara-Sa-Uk]

According to point 2, you mentioned that your SVM code is based on GMM Super vectors, but the code seems to be based on HMM Hidden Markov Model, I have changed every thing from HMM to GMM and it works fine so is what I did correct?

[SuperKogito]

• I think this is a a mistake from my side, I was convinced that I used GMM with SVM but it seems that I am using HMM.
  I think either one should work fine but yes changing the HMM call to GMM should be it, so you did well 👏 . I will review the code soon and publish the fix for this along with some improvements I have been working on. Thank you for raising this point :)

• To Help you understand super-vectors and GMM better; here what the system looks like when modeled(Think of the UBM here as a GMM, after all a UBM is just a one big GMM.):
  
  source: The present and future of voiceprint based security.pdf