Currently I'm feeding spectrogram of audio to the CNN with 3 convolution.
Each convolution is followed by a max pool of filter size 2.
First -> 5x5x4
Second - > 5x5x8
Third - > 5x5x16
and final layer is a fully connected with 512 unit.
But while training with dropout of 0.25, getting train accuracy of 0.97 with 150 iterations. and on test data accuracy is just 0.60.
Tell me how to improve the results.
Yes both train and test data come from same distribution.