# DadaGP: A Dataset of Tokenized GuitarPro Songs for Sequence Models

arXiv: https://arxiv.org/abs/2107.14653 · HTML: https://mlsanity.com/paper/2107.14653/

## Key facts

- Cited by 20 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 46 references that are in the map.
- First posted on arXiv 30 Jul 2021.

## Builds on (most cited first, 18 of 18)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Pointer Sentinel Mixture Models](https://mlsanity.com/paper/1609.07843/) (2016)
- [Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context](https://mlsanity.com/paper/1901.02860/) (2019)
- [Generating Long Sequences with Sparse Transformers](https://mlsanity.com/paper/1904.10509/) (2019)
- [Jukebox: A Generative Model for Music](https://mlsanity.com/paper/2005.00341/) (2020)
- [Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Dataset](https://mlsanity.com/paper/1810.12247/) (2018)
- [Music Transformer](https://mlsanity.com/paper/1809.04281/) (2018)
- [Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs](https://mlsanity.com/paper/2101.02402/) (2021)
- [Cutting Music Source Separation Some Slakh: A Dataset to Study the Impact of Training Data Quality and Quantity](https://mlsanity.com/paper/1909.08494/) (2019)
- [POP909: A Pop-song Dataset for Music Arrangement Generation](https://mlsanity.com/paper/2008.07142/) (2020)
- [MusPy: A Toolkit for Symbolic Music Generation](https://mlsanity.com/paper/2008.01951/) (2020)
- [GiantMIDI-Piano: A large-scale MIDI dataset for classical piano music](https://mlsanity.com/paper/2010.07061/) (2020)
- [Symbolic Music Genre Transfer with CycleGAN](https://mlsanity.com/paper/1809.07575/) (2018)
- [Automatic Composition of Guitar Tabs by Transformers and Groove Modeling](https://mlsanity.com/paper/2008.01431/) (2020)
- [The NES Music Database: A multi-instrumental dataset with expressive performance attributes](https://mlsanity.com/paper/1806.04278/) (2018)
- [Musical Composition Style Transfer via Disentangled Timbre Representations](https://mlsanity.com/paper/1905.13567/) (2019)
- [Deep Composer Classification Using Symbolic Representation](https://mlsanity.com/paper/2010.00823/) (2020)
- [Composer Style Classification of Piano Sheet Music Images Using Language Model Pretraining](https://mlsanity.com/paper/2007.14587/) (2020)

## Built on by (most cited first, 20 of 20)

- [GTR-CTRL: Instrument and Genre Conditioning for Guitar-Focused Music Generation with Transformers](https://mlsanity.com/paper/2302.05393/) (2023)
- [Natural Language Processing Methods for Symbolic Music Generation and Information Retrieval: a Survey](https://mlsanity.com/paper/2402.17467/) (2024)
- [YM2413-MDB: A Multi-Instrumental FM Video Game Music Dataset with Emotion Annotations](https://mlsanity.com/paper/2211.07131/) (2022)
- [The GigaMIDI Dataset with Features for Expressive Music Performance Detection](https://mlsanity.com/paper/2502.17726/) (2025)
- [GOAT: A Large Dataset of Paired Guitar Audio Recordings and Tablatures](https://mlsanity.com/paper/2509.22655/) (2025)
- [ProgGP: From GuitarPro Tablature Neural Generation To Progressive Metal Production](https://mlsanity.com/paper/2307.05328/) (2023)
- [MIDI-to-Tab: Guitar Tablature Inference via Masked Language Modeling](https://mlsanity.com/paper/2408.05024/) (2024)
- [Moonbeam: A MIDI Foundation Model Using Both Absolute and Relative Music Attributes](https://mlsanity.com/paper/2505.15559/) (2025)
- [A Data-Driven Methodology for Considering Feasibility and Pairwise Likelihood in Deep Learning Based Guitar Tablature Transcription Systems](https://mlsanity.com/paper/2204.08094/) (2022)
- [Between the AI and Me: Analysing Listeners' Perspectives on AI- and Human-Composed Progressive Metal Music](https://mlsanity.com/paper/2407.21615/) (2024)
- [From Words to Music: A Study of Subword Tokenization Techniques in Symbolic Music Generation](https://mlsanity.com/paper/2304.08953/) (2023)
- [Modeling Bends in Popular Music Guitar Tablatures](https://mlsanity.com/paper/2308.12307/) (2023)
- [Subtractive Training for Music Stem Insertion using Latent Diffusion Models](https://mlsanity.com/paper/2406.19328/) (2024)
- [Fretting-Transformer: Encoder-Decoder Model for MIDI to Tablature Transcription](https://mlsanity.com/paper/2506.14223/) (2025)
- [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)
- [Exploring Procedural Data Generation for Automatic Acoustic Guitar Fingerpicking Transcription](https://mlsanity.com/paper/2508.07987/) (2025)
- [A Machine Learning Approach for MIDI to Guitar Tablature Conversion](https://mlsanity.com/paper/2510.10619/) (2025)
- [Playability-Aware Audio-to-Tablature Guitar Transcription via Diffusion Models](https://mlsanity.com/paper/2608.30854/) (2026)
- [TART: A Modular Tool for Technique-Aware Audio-to-Tablature Guitar Transcription](https://mlsanity.com/paper/2609.11904/) (2026)

## Abstract (arXiv)

Originating in the Renaissance and burgeoning in the digital era, tablatures are a commonly used music notation system which provides explicit representations of instrument fingerings rather than pitches. GuitarPro has established itself as a widely used tablature format and software enabling musicians to edit and share songs for musical practice, learning, and composition. In this work, we present DadaGP, a new symbolic music dataset comprising 26,181 song scores in the GuitarPro format covering 739 musical genres, along with an accompanying tokenized format well-suited for generative sequence models such as the Transformer. The tokenized format is inspired by event-based MIDI encodings, often used in symbolic music generation models. The dataset is released with an encoder/decoder which converts GuitarPro files to tokens and back. We present results of a use case in which DadaGP is used to train a Transformer-based model to generate new songs in GuitarPro format. We discuss other relevant use cases for the dataset (guitar-bass transcription, music style transfer and artist/genre classification) as well as ethical implications. DadaGP opens up the possibility to train GuitarPro score generators, fine-tune models on custom data, create new styles of music, AI-powered songwriting apps, and human-AI improvisation.