
Mapping the World of Music Using Machine Learning: Part 1 - ravimody
https://tech.iheart.com/mapping-the-world-of-music-using-machine-learning-part-1-9a57fa67e366
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6stringmerc
iHeart Radio? The child of Clear Channel? The conglomerate that bought up all
sorts of regional stations and homogenized them to the point of seemingly
choking regional sounds and styles in the favor of slick, corporate approved
campaigns to consolidate listeners into pens like cattle to the slaughter[1]?

My take, as a musician, is that this isn't about helping listeners find "Music
they love" \- if it does happen, a lucky accident for the listener. It's
fundamentally trying to exploit algorithms and human nature to be able to
charge more for ad space. The business hates risk, and this modelling and
"learning" is simply to reduce their risk of playing a track that might
encourage a person to, you know, change the station.

This may sound extremely cynical, but it's hard to deny that Clear Channel is
a very spurious company playing the same old "We love music and musicians"
card when they're really talking about their own profits.

[1] Just one article - it's been covered time and again.
[http://www.daveyd.com/articlesclearchannelbyjeffpearlstein.h...](http://www.daveyd.com/articlesclearchannelbyjeffpearlstein.html)

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jamminontheone
From what I remember Clear Channel purchased a company called Thumbplay and
rolled it into iHeart Radio to build out their web app. The developers that
they acquired with that purchase whom I've met legitimately are music fans and
had very mixed feelings about having to work for Clear Channel.

Just an anecdote, I totally agree with your sentiment.

~~~
6stringmerc
Oh I can understand! I'd feel for their plight too; it took me a while to get
out from a couple gigs that I had principles in conflict with, so "doing it
for the paycheck" isn't a light subject. Thanks for sharing, especially as a
reminder that where we start and why we start may not be where we end up in
the long-run.

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guelo
I must be weird because I like music across a wide range of styles,
electronica, rock, rap, r&b, pop, world, and all mixtures of them. I get bored
being stuck in an algorithmic bubble with similar sounding music for too long.
I like music that is "interesting, according to me" but I can't really define
interesting until I listen to it.

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ravimody
I'm similar - I have an eclectic taste in music that is often not served well
by static, long-term algorithms that place me into a "well" of the same
sounding music. It's a problem I think about a lot.

Matrix factorization can deal with this a bit by using the high dimensional
space to place your tastes into an area that reflects many different styles at
the same time. In part 2 of the blog post we're going to talk about how we're
modeling the acoustic qualities of music, which can find common patterns from
completely different genres (for example, you may like soothing music with
female vocals in both jazz and indie rock). In part 3 we'll talk a bit about
how we can combine recent signals (like thumbs) to take into account your
current mood, which I find helps pinpoint interesting music to surface right
now.

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chestervonwinch
> we're going to talk about how we're modeling the acoustic qualities of
> music, which can find common patterns from completely different genres

That's neat! I was curious of this is / was being looked into. It seems like I
often get music that's matched based on a demographic (if that makes sense),
rather than music matched on the characteristic features of the current song /
band.

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vintermann
What we call genre is sometimes circumscribed by stylistic elements, sometimes
by subculture (demographics as seen from the listeners' own perspective). But
quite often since the rise of radio, it's circumscribed by target demographic
as seen from advertisers' perspective.

The worst case of that is probably "new age", a label rejected by virtually
all the artists so labeled (and most of the listeners), and having no common
traits to speak of, but lumped together as whatever sold better in bookstores
than in record stores.

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3dfan
Reminds me of [http://www.music-map.com](http://www.music-map.com) which is
pretty useful to discover new music.

~~~
placebo
I created something similar a couple of years ago:
[http://www.nocurve.com/musicmap/](http://www.nocurve.com/musicmap/)

If anyone is interested in how it was implemented: [http://nocurve.com/fun-
with-data/data-mining-on-freedb/](http://nocurve.com/fun-with-data/data-
mining-on-freedb/)

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Dramatize
Spotify's Discover Weekly playlist is doing a great job creating a mixtape of
new music. It's the best example of 'you might also like' I've seen.

~~~
6stringmerc
Glad to hear you like it, because I think in some foreign countries (according
to my accounting) their system is introducing my material at a respectable
rate. They aren't getting 'pushed' like based on an ad campaign, spike-and-
valley style. It's much more that one or two listens might happen - granted,
this could be from other 'touch points' but going back in time before I was as
coordinated account wise. Can't claim it as fact, but gut instinct I suppose.

