Excellent article! I think it has the right level of detail, one question though: why the shape of the tensor? 4x8x11.

That I didn't get from the text.

the spectrograms are 128x173 (128 mel frequency bins by 173 time frames) the encoder is downsampling 4 stages of stride 2 convolutions so it halves dimensions 4 times

0: 128 x 173

1: 64 x 87

2: 32 x 44

3: 16 x 22

4: 8 x 11

Then i used 4 separate channels.

This was somewhat arbitrary due to the local training constraint. This would be a hyper parameter worth tuning if I had time to dig into this more.

I trained this a few month ago and don't remember exactly what I tried before I arrived here, but I only ran the whole process 2 or 3 times because of how long it took to train. Hope this answers your question!