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 asmd``
Other examples in the paper!
.. _docs: https://asmd.readthedocs.org
Changelog
=========
Version 0.5
^^^^^^^^^^^
#. Improved inference of misalignments
#. Improved the reproducibility of artificial data
#. Improved the documentation
#. Added `ASAP` group in **Maestro: broken backward compatibility**
#. Added `score` for the original score
#. Added midi note matching based on EITA method
#. Added missing and extra notes
#. General refactoring
#. Added functions for set operations among datasets (union, intersections,
complement and subsampling)
#. Various fixes
Version 0.4
^^^^^^^^^^^
# Skipped
Version 0.3
^^^^^^^^^^^
#. Fixed MIDI values ([0, 128) for control changes and pitches)
#. Fixed metadata error while reading audio files
#. Fixed pedaling for tracks that have no pedaling
#. Fixed group selection
#. Added `get_songs`
#. Improved initialization of `Dataset` objects
#. Improved documentation
Version 0.2.2-2
^^^^^^^^^^^^^^^
#. Fixed major bug in install script
#. Fixed bug in conversion tool
#. Removed TRIOS dataset because no longer available
#. Updated ground_truth
Version 0.2.2
^^^^^^^^^^^^^
#. Improved ``parallel`` function
#. Improved documentation
#. Various fixings in ``get_pedaling``
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 matching of same music piece among different datasets
#. Added `torch.DatasetDump` for preprocessing datasets and use them in pytorch
#. Add new modalities (video, images)
#. Add other datasets
#. Refactoring of the `filter` function (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_
.. _arXiv:2003.01958: https://arxiv.org/abs/2003.01958
---
Federico Simonetta
#. https://federicosimonetta.eu.org
#. https://lim.di.unimi.it