WaivOps RGTM-PNO: Open Audio Resources for Machine Learning in Music

RGTM-PNO Dataset

RGTM-PNO is an open audio dataset featuring a collection of vintage piano songs in the style of ragtime, a genre that flourished around the turn of the 20th century. The dataset contains 262 audio tracks recorded in uncompressed stereo WAV format, synthetically generated using a custom soundfont and MIDI files sourced from public resources online.

Dataset

The primary objective of this dataset is to provide accessible content for machine learning applications in music and audio research. Some potential use cases for this dataset include audio classification, automatic music transcription (ADT), music information retrieval (MIR), melody analysis, AI music generation, sound design and signal processing.

Specifications

• 262 piano songs (approximately 13.5 hours)
• 16-bit WAV format
• Tempo: 120bpm (live performance in absolute time)
• Variational chorus detuning (vintage piano sound)
• Paired audio and MIDI data

License

This dataset was compiled by WaivOps, a crowdsourced music project managed by the sound label company Patchbanks. The audio recordings were sonified from MIDI files containing historical musical compositions believed to be in the public domain and copyright free.

The RGTM-PNO dataset is licensed under Creative Commons Attribution 4.0 International (CC BY 4.0).

Additional Info

For audio examples or more information about this dataset, please refer to the GitHub repository.