add readme

README.md

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+---
+license: cc-by-nc-sa-4.0
+language:
+- en
+tags:
+- music
+- midi
+- piano
+- classification
+pretty_name: Aria-MIDI
+size_categories:
+- 1M<n<10M
+---
+# The Aria-MIDI Dataset
+
+[Paper](https://openreview.net/pdf?id=X5hrhgndxW) / [Blog](https://loubbrad.com/blog/ariamidi) 
+
+The Aria-MIDI dataset is a collection of 1,186,253 MIDI files, comprising approximately 100,629 hours of transcribed solo-piano recordings, with metadata in categories including genre, composer, performer, as well as compositional identifiers. We developed Aria-MIDI to serve as dataset for pre-training generative music models, and are releasing it with the goal of facilitating open research in music information retrieval and generative modelling for symbolic music.
+
+## Download (V1)
+
+Along with the full dataset, we provide several subsets which may be appropriate for different use cases: 
+
+| Subset        | # Files   | De-duplication[^1] | Pre-processing filters[^2]        | Example Application                    |
+|---------------|-----------|--------------------|------------------------------------|----------------------------------------|
+| Full [[download](https://huggingface.co/datasets/loubb/aria-midi/resolve/main/aria-midi-v1-ext.tar.gz?download=true)]       | 1,186,253 | No                 | None                               | Data analysis                          |
+| Pruned [[download](https://huggingface.co/datasets/loubb/aria-midi/resolve/main/aria-midi-v1-pruned-ext.tar.gz?download=true)]     | 820,944   | 10                 | Light                              | Foundation model pre-training          |
+| Deduped [[download](https://huggingface.co/datasets/loubb/aria-midi/resolve/main/aria-midi-v1-deduped-ext.tar.gz?download=true)]    | 371,053   | 1                  | Heavy                              | Generative modelling                   |
+| Unique [[download](https://huggingface.co/datasets/loubb/aria-midi/resolve/main/aria-midi-v1-unique-ext.tar.gz?download=true)]     | 32,522    | 1                  | Compositional metadata[^3]         | Composition fingerprints               |
+
+[^1]: For popular composers, we retain at most *X* instances per opus/piece-number pair and discard files lacking compositional identifiers.  
+[^2]: Heuristic-based filtering, considering note density, pitch and duration entropy, silence, number of segments, and indicators of repetitive content, to exclude problematic entries.  
+[^3]: Exclude all files lacking exact compositional identifiers.
+
+## Citation/License
+
+Aria-MIDI is distributed with the [CC-BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en) license. By accessing this dataset, you declare that you agree to our [disclaimer](https://github.com/loubbrad/aria-midi/blob/main/disclaimer.md). If you use the dataset, or any of the components in our data-pipeline, please cite the paper where they were introduced:
+
+```
+@inproceedings{bradshawaria,
+  title={Aria-MIDI: A Dataset of Piano MIDI Files for Symbolic Music Modeling},
+  author={Bradshaw, Louis and Colton, Simon},
+  booktitle={International Conference on Learning Representations},
+  year={2025},
+  url={https://openreview.net/forum?id=X5hrhgndxW}, 
+}
+```