# ProgGP: From GuitarPro Tablature Neural Generation To Progressive Metal Production

arXiv: https://arxiv.org/abs/2307.05328 · HTML: https://mlsanity.com/paper/2307.05328/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 25 references that are in the map.
- First posted on arXiv 11 Jul 2023.

## Builds on (most cited first, 12 of 12)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context](https://mlsanity.com/paper/1901.02860/) (2019)
- [Music Transformer](https://mlsanity.com/paper/1809.04281/) (2018)
- [Music FaderNets: Controllable Music Generation Based On High-Level Features via Low-Level Feature Modelling](https://mlsanity.com/paper/2007.15474/) (2020)
- [MusPy: A Toolkit for Symbolic Music Generation](https://mlsanity.com/paper/2008.01951/) (2020)
- [Music transcription modelling and composition using deep learning](https://mlsanity.com/paper/1604.08723/) (2016)
- [Convolutional Generative Adversarial Networks with Binary Neurons for Polyphonic Music Generation](https://mlsanity.com/paper/1804.09399/) (2018)
- [DadaGP: A Dataset of Tokenized GuitarPro Songs for Sequence Models](https://mlsanity.com/paper/2107.14653/) (2021)
- [Automatic Composition of Guitar Tabs by Transformers and Groove Modeling](https://mlsanity.com/paper/2008.01431/) (2020)
- [GTR-CTRL: Instrument and Genre Conditioning for Guitar-Focused Music Generation with Transformers](https://mlsanity.com/paper/2302.05393/) (2023)
- [Exploring Conditioning for Generative Music Systems with Human-Interpretable Controls](https://mlsanity.com/paper/1907.04352/) (2019)
- [LooperGP: A Loopable Sequence Model for Live Coding Performance using GuitarPro Tablature](https://mlsanity.com/paper/2303.01665/) (2023)

## Built on by (most cited first, 4 of 4)

- [GOAT: A Large Dataset of Paired Guitar Audio Recordings and Tablatures](https://mlsanity.com/paper/2509.22655/) (2025)
- [Between the AI and Me: Analysing Listeners' Perspectives on AI- and Human-Composed Progressive Metal Music](https://mlsanity.com/paper/2407.21615/) (2024)
- [GuitarFlow: Realistic Electric Guitar Synthesis From Tablatures via Flow Matching and Style Transfer](https://mlsanity.com/paper/2510.21872/) (2025)
- [Guitar Chord Diagram Suggestion for Western Popular Music](https://mlsanity.com/paper/2407.14260/) (2024)

## Abstract (arXiv)

Recent work in the field of symbolic music generation has shown value in using a tokenization based on the GuitarPro format, a symbolic representation supporting guitar expressive attributes, as an input and output representation. We extend this work by fine-tuning a pre-trained Transformer model on ProgGP, a custom dataset of 173 progressive metal songs, for the purposes of creating compositions from that genre through a human-AI partnership. Our model is able to generate multiple guitar, bass guitar, drums, piano and orchestral parts. We examine the validity of the generated music using a mixed methods approach by combining quantitative analyses following a computational musicology paradigm and qualitative analyses following a practice-based research paradigm. Finally, we demonstrate the value of the model by using it as a tool to create a progressive metal song, fully produced and mixed by a human metal producer based on AI-generated music.