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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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WaivOps RGTM-PNO: Open Audio Resources for Machine Learning in Music

Authors: Patchbanks; WaivOps;

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

Abstract

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.

Keywords

automatic music transcription, Music information retrieva, Audio, audio classification, AI Music, MIDI Datasets, MIR, Symbolic Music Generation, MIDI, ADT

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average