Idea: Music connectome project (finding novel relationships between music)

Wikipedia:

A connectome is a comprehensive map of neural connections in the brain, and may be thought of as its “wiring diagram”… A connectome is constructed by… mapping where neurons are connected through synapses…

Hmm, what about mapping connections between music, songs, artists, even albums?

In music, as in synapses:

There are strong natural constraints on which neurons or neural populations can interact, or how strong or direct their interactions are.

In music these constraints are tonal, mappings to scales, desirable chord progressions, etc. Obviously you can go from any note to any other, but if you do that planlessly enough, you’ll lose your audience pretty quickly. :smile: The rules of what (generally) sounds good are well enough understood, and the entire field of “Music Theory” exists for that purpose. But simply learning music theory doesn’t let you make good music, and indeed “good” is also highly subjective, so clearly something more is needed to understand not only what is good, but what is good for each person.

What better way to approach this than to ask them?.. Sort of.

Concept

A project with (theoretically) similar goals to the Music Genome Project which gave birth to Pandora. Essentially, to “take apart” music and figure out what makes it work, what makes people like a certain song, artist, band, etc. However, instead of the “experts” approach of the MGP, this would be based on crowd sourcing. Although crowd sourcing is not an all-purpose tool, when it comes to determining what people like and, potentially, why, a good place to start is asking people what they like.

The MDP would seek to collect information about people’s likes and dislikes, especially for specific songs and their components (e.g. vocal, beat, etc.), and potentially collect similar relevant information about bands, albums, etc. This would be accomplished through a free-to-access website with a song rating and comment system.

Inspiration

This project is somewhat inspired by the current popularity of music “suggestion” services like Pandora, Last.fm, etc. From my experience so far all the currently available options fail to make good suggestions for more complex, nuanced, or specific starting criteria. For example, let’s say you like one or two Beyonce songs, but you don’t like all Beyonce songs, nor songs by Destiny’s Child (of which Beyonce is a former member). How does Pandora determine what songs to play if you enter Beyonce’s “Halo”, given this unique preference? Pandora does not allow you to specify the things you like or dislike about a particular song or artist, so it will naturally assume you like the artist, which in many cases is actually not true. Musical taste is more complex than this, especially with the focus on singles releases, popularity charts, etc. The ability to better communicate one’s preferences and musical taste is also critical when considering more complex or varied artists, e.g. Pink Floyd or The Kinks, or when considering “One Hit Wonders”, e.g. The Flys (“Got You Where I Want You”).