I have a 2 dimensional data in the form of a text file. I have to build a GMM based on this data using Sidekit 1.2.
Which function should I use to estimate the parameters of the Gaussian model (Mean, covariance matrix, weighted average etc.)
Can you please provide a small example with your own set of (x,y) data and build a GMM using that ?
Any help would be greatly appreciated.
Sidekit is a toolkit built mainly for the task of speaker recognition, and its framework (as other similar toolkits) relies on the training data consisting of audio files in the formats .wav, .sph or raw PCM. If you're just building a GMM and don't plan to use it for speaker recognition experiments, I would recommend using another toolkit for general statistical purposes (scikit-learn might be a good choice).
If you do plan to do speaker recognition tasks, you will have to some initial work on your data. If your text-data is some form of speaker data, you could convert it to the appropriate format. For example, if the y part is raw audio, convert it to wav-files. If y is cepstral features or other features, store it in h5.-format. After doing this, you can build a GMM for speaker recognition tasks by following the tutorials on the Sidekit homepage.