A lot of studies feed MFCCs as well as MFCC delta and double deltas directly to a CNN for audio classification. My question is, are the MFCC Deltas concatenated with the MFCC matrix? Most papers simply state they used MFCC + MFCC Delta + MFCC Double Delta and the plus sign is left to interpretation!


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Yes, the delta and delta-delta variants are concatenated. However the details may vary a bit based on model type:

If the model takes a 1d (features,) input (such as a multi-layer-perceptron, logistic regression, random forest etc), then the delta coefficients are concatenated. So features is [mfcc1,mfcc2...,dmfcc1,dmfcc2... ].

For a model that takes 2d (time,features) input like a RNN, then it is concatenated on the features axis.

For a model that takes 3d (time,features,channels) inputs like a CNN, then the delta coefficients are usually its own plane in the channels dimensions. This ensures that the delta MFCC coefficient is in the same time x feature position as the corresponding MFCC coefficient, which is easiest for the convolutional kernel to exploit.


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