Images are only correlated on very small space/time scales. Audio/Music has correlation on multiple over-lapping time scales. We know this is true because Video filters are usually very small, bilinear, bi-cubic, operating on only a very small region. A large video filter doesn't make sense because there is no correlation. Audio requires attention to tone, transients, harmonics, voice envelopes, relationships between notes/scales, rhythym, recurring musical passages etc. etc. All these require filtering, or memory based processing over different time scales. So audio/music from a raw data perspective is much more difficult for an AI system compared to images. This is why image related AI is so prevalant, it is the low-hanging fruit due to small amount of correlation that the Neural Net needs to deal with.