AcousticBrainz/Ideas

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< AcousticBrainz
Revision as of 09:17, 22 February 2016 by Alastairp (talk | contribs) (intro, another project)

This page describes ideas that we've had for AcousticBrainz project. If you are interested in working on them for Summer of Code, or as part of the MusicBrainz project, [Communication contact us] through the MusicBrainz IRC channels. If you want to explore this data in an academic context, talk to the Music Technology Group.

Data exploration

An interactive system to explore the data that we already have in AcousticBrainz. For example, what are all of the songs that we say are in a certain Key. Order these by tempo and then group them by mood.

Search

A search system (which could be part of the above task) that lets you search for tracks by their metadata or by extracted features. This could use an existing search technology (e.g. Solr), or something custom-written for the task. A similar task would be to be able to place songs in an n-dimensional similarity space to explore songs that are acoustically similar.

Data accuracy

An investigation of the accuracy of AcousticBrainz compared to other music databases. For example, MusicBrainz has many tags which represent genres. This information is also available from services like Last.fm. Lower-level information such as key and bpm is available from services such as the Echo Nest.

Investigate content-based similarity

In the Freesound project we use essentia and gaia, two main components of AcousticBrainz to compute the acoustic similarity between sound samples. We want to do something similar with AcousticBrainz. Some questions to be answered in this project are:

* Can Gaia perform similarity between all 3 million tracks in the AB database, or do we need another technology like solr
* Are duplicate submissions of the same song using different codecs very similar? If not, why not? Can we use this similarity to discover songs with incorrectly tagged MBIDs or the same song with two different MBIDs?
* Are there some songs which act as "Hub songs" - that is, they are similar to many other songs

odd one out