Yeah. But  but wait a minute. You may not need to re uh uh retrain the m model. You just may n may need to c uh give uh less weight to  to uh a mod uh a component of the model which represents this particular feature. You don't have to retrain it.
Oh. So if you  Instead of altering the feature vectors themselves , you  you modify the  the  the Gaussians in the models.
You just multiply. Yeah. Yep. You modify the Gaussian in the model , but in the  in the test data you would have to put it in the power , but in a training what you c in a training uh  in trained model , all you would have to do is to multiply a model by appropriate constant.
Uh - huh. But why  if you 're  if you 're multi if you 're altering the model , why w in the test data , why would you have to muck with the uh cepstral coefficients ?