  We use a modified SampleRNN architecture to generate music in modern genres
such as black metal and math rock. Unlike MIDI and symbolic models, SampleRNN
generates raw audio in the time domain. This requirement becomes increasingly
important in modern music styles where timbre and space are used
compositionally. Long developmental compositions with rapid transitions between
sections are possible by increasing the depth of the network beyond the number
used for speech datasets. We are delighted by the unique characteristic
artifacts of neural synthesis.
