The conventions we use for dimensions are given in the README 3. In particular, a waveform is (channel, time), and MFCC : (channel, time) -> (channel, mfcc, time), and so MFCC is applied per channel. Your original waveform must therefore have had 2 channels.
In the datasets we provide, the number of channels are the same across all waveforms.
Since the output of MFCC is just a tensor, you can use torch.cat to concatenate two MFCCs along a given axis.
Is that what you were asking?