Alright , now I 'm just slightly impressed , OK.
Um. Yeah , basically the observation is what we discussed already. The MSG problem , um , the fact that the MLP trained on target task decreased the error rate. but when the M - MLP is trained on the um  is not trained on the target task , it increased the error rate compared to using straight features. Except if the features are bad  uh , actually except if the features are not correctly on - line normalized. In this case the tandem is still better even if it 's trained on  not on the target digits.
Yeah. So it sounds like  yeah , the net corrects some of the problems with some poor normalization.
Yeah.