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---
language:
- en
license: cc-by-4.0
dataset_info:
features:
- name: id
dtype: string
- name: start_time
dtype: int32
- name: question
dtype: string
- name: question_type
dtype: string
- name: answer
dtype: string
splits:
- name: train
num_bytes: 1510405
num_examples: 1779
download_size: 114117
dataset_size: 1510405
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# URMP ABC Notation 25s Dataset
## Dataset Summary
The **URMP ABC Notation 25s Dataset** is a collection of question-and-answer pairs based on short audio clips from the [University of Rochester Multi-Modal Music Performance (URMP) dataset](https://labsites.rochester.edu/air/projects/URMP.html). Each entry in the dataset provides:
- An `id` identifying the original audio file.
- A `start_time` indicating where the audio clip begins within the full audio file.
- A `question` generated to prompt music transcription via ABC notation.
- An `answer` which is the ABC notation.
This dataset is intended for training multi-modal audio-language models (like [Spotify Llark](https://research.atspotify.com/2023/10/llark-a-multimodal-foundation-model-for-music/) and [Qwen2-Audio](https://github.com/QwenLM/Qwen2-Audio)) on the task of music transcription. The code I used for converting the MIDI to ABC notation is based on [this script](https://github.com/jwdj/EasyABC/blob/master/midi2abc.py).
**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
- **URMP Dataset:** The original audio files are part of the URMP dataset. Refer to the [URMP dataset license](https://labsites.rochester.edu/air/projects/URMP.html) for terms of use.
## Citation Information
If you use this dataset, please cite it as follows:
```bibtex
@dataset{urmp_abc_notation_25s_2024,
title={URMP ABC Notation Dataset},
author={Jon Flynn},
year={2024},
howpublished={\url{https://huggingface.co/datasets/jonflynn/urmp_abc_notation_25s}},
note={ABC notation for the URMP dataset split into 25 second chunks},
}
```
Additionally, cite the original URMP dataset:
```bibtex
@article{li2018creating,
title={Creating a Multimodal Dataset for Tracking Human Motion and Kinematics in Music Performances},
author={Li, Chenyu and Xia, Wei and Akbari, Vahid and Duan, Zhiyao and Xu, Chenliang},
journal={arXiv preprint arXiv:1807.09365},
year={2018}
}
```
---
**Additional Resources:**
- **URMP Dataset Website:** [URMP Dataset](https://labsites.rochester.edu/air/projects/URMP.html)
- **ABC Notation:** [ABC Notation Official Website](http://abcnotation.com/) |