# incremental gaussian mixture model [closed]

I have trained GMM on small train data set, I would like to update the GMM parameters on the fly when new samples arrive. Please direct on how to do that? Please inform if some existing implementation exits in python

dataset is speech utterance, and I would like to update the parameters of the model of a speaker, as new utterances are added instead of re-training with the entire data.

## closed as too broad by Ben, kjetil b halvorsen, Ferdi, mdewey, Peter Flom♦Dec 27 '18 at 11:35

Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

• Can you give more details about the model you are using and the data-set? – mdewey Aug 9 '16 at 8:19
• details are added. Please provide suggestions ! – Shreya Aug 9 '16 at 9:05

For each new batch, they use covariance and Hotelling's $T^2$ tests to decide if it is needed to merge equivalent clusters.