# Generating Black Metal and Math Rock: Beyond Bach, Beethoven, and Beatles

arXiv: https://arxiv.org/abs/1811.06639 · HTML: https://mlsanity.com/paper/1811.06639/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Nov 2018.

## Built on by (most cited first, 2 of 2)

- [The GigaMIDI Dataset with Features for Expressive Music Performance Detection](https://mlsanity.com/paper/2502.17726/) (2025)
- [LoopNet: Musical Loop Synthesis Conditioned On Intuitive Musical Parameters](https://mlsanity.com/paper/2105.10371/) (2021)

## Abstract (arXiv)

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.