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jonflynn/maestro_abc_notation_25s

Maestro ABC Notation 25s Dataset Dataset Summary This is based on V3.0.0 of the Maestro dataset. The Maestro ABC Notation 25s Dataset is a curated collection of question-and-answer pairs derived from short audio clips within the MAESTRO dataset. Each entry in the dataset includes: An id corresponding to the original audio file. A start_time marking where the 25-second audio clip begins within the full track. A question designed to prompt music transcription in… See the full description on the dataset page: https://huggingface.co/datasets/jonflynn/maestro_abc_notation_25s.

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Maestro ABC Notation 25s Dataset

Dataset Summary

This is based on V3.0.0 of the Maestro dataset.

The Maestro ABC Notation 25s Dataset is a curated collection of question-and-answer pairs derived from short audio clips within the MAESTRO dataset. Each entry in the dataset includes:

  • —An id corresponding to the original audio file.
  • —A start_time marking where the 25-second audio clip begins within the full track.
  • —A question designed to prompt music transcription in ABC notation.
  • —An answer that provides the transcription in ABC notation format.

This dataset is crafted for training multi-modal audio-language models (such as Spotify Llark and Qwen2-Audio) with a focus on music transcription tasks. The MIDI-to-ABC conversion is achieved with a modified script based on this code.

Why ABC?

The reasons for choosing this notation are:

  • —It's a minimalist format for writing music
  • —It's widely used and popular, language models already have good comprehension and know a lot about ABC notation.
  • —It's flexible and can easily be extended to include tempo changes, time signature changes, additional playing styles like mentioned above, etc…

Dataset Modifications to ABC Format

  • —Default octaves have been assigned to each instrument, using their most commonly played range. This reduces redundant octave notation.
  • —For consistency, I excluded pieces that contain time signature changes or significant tempo variations (greater than 10 BPM).
  • —All samples in this dataset contain active musical parts - sections with complete silence have been removed.

Licensing Information

  • —MAESTRO Dataset: The audio files are sourced from the MAESTRO dataset, licensed under the Creative Commons Attribution Non-Commercial Share-Alike 4.0 license. Please refer to the MAESTRO dataset page for full licensing details.

Citation Information

If you utilize this dataset, please cite it as follows:

bibtex
@dataset{maestro_abc_notation_25s_2024,
  title={MAESTRO ABC Notation Dataset},
  author={Jon Flynn},
  year={2024},
  howpublished={\url{https://huggingface.co/datasets/jonflynn/maestro_abc_notation_25s}},
  note={ABC notation for the MAESTRO dataset split into 25-second segments},
}

For the original MAESTRO dataset, please cite the following:

bibtex
@inproceedings{hawthorne2018enabling,
  title={Enabling Factorized Piano Music Modeling and Generation with the {MAESTRO} Dataset},
  author={Curtis Hawthorne and Andriy Stasyuk and Adam Roberts and Ian Simon and Cheng-Zhi Anna Huang and Sander Dieleman and Erich Elsen and Jesse Engel and Douglas Eck},
  booktitle={International Conference on Learning Representations},
  year={2019},
  url={https://openreview.net/forum?id=r1lYRjC9F7},
}