# Understanding GMM-MMI

While studying Gaussian mixture models and the expectation maximization algorithm, I also came across a number of studies that used 'Discriminative training' for the models that addressed some limitations of the EM algorithm. In particular, the use of maximum mutual information is quite common.

I understand the basic idea behind maximizing mutual information; however, I am unable to find any source that gives the equations involved in estimating the means, variances, mixing parameters and the predicted labels.

Can you please state them along with an explanation?

• MLE is the usual thing. The one paper I found that "introduced" MMI has 4 citations. Why do you think this is "quite common"? Jun 11 '18 at 6:13
• I've seen more than one publication using mmi. It is quite common in speech recognition. Jun 11 '18 at 6:58