Audio-Score Meta-Dataset
Project description
Audio-Score Meta-Dataset
ASMD is a framework for installing, using and creating music multimodal datasets including (for now) audio and scores.
This is the repository for paper [1]
Read more in the docs.
To install: pip install asmd
To install datasets: python -m asmd.install
To import API: from asmd import audioscoredataset as asd
Other examples in the paper!
Changelog
Version 0.2.1
Added nframes utility to compute the number of frames in a given time lapse
Added group attribute to each track to create splits in a dataset (supported in only Maestro for now)
Changed .pyx to .py with cython in pure-python mode
Version 0.2
Added parallel utility to run code in parallel over a while dataset
Added get_pianoroll utility to get score as pianoroll
Added sustain, sostenuto, and soft to model pedaling information
Added utilities frame2time and time2frame to ease the development
Added get_audio_data to get data about audio without loading it
Added get_score_duration to get the full duration of a score without loading it
Added another name for the API: from asmd import asmd
Deprecated from asmd import audioscoredataset
Changed the generate_ground_truth command line options
Easier to generate misaligned data
Improved documentation
Roadmap
Add new modalities (video, images)
Improve the artificial misalignment
Add datasets for the artificial misalignment (e.g. ASAP, Giant-Midi Piano)
Add other datasets
Refactoring of the API (it’s a bit long now…)
Cite us
[1] Simonetta, Federico ; Ntalampiras, Stavros ; Avanzini, Federico: ASMD: an automatic framework for compiling multimodal datasets with audio and scores. In: Proceedings of the 17th Sound and Music Computing Conference. Torino, 2020 arXiv:2003.01958
—
Federico Simonetta
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