Archive for category Music

Creative hacking

My hack at the MIDEM Music Hack Day this year is what I’d call a Creative Hack. I built it, not because it answered any business use case or because it demonstrated some advanced capability of some platform or music tech ecosystem, I built it because I was feeling creative and I wanted to express my creativity in the best way that I can which is to write a computer program. The result is something I’m particularly proud of. It’s a dynamic visualization of the song Burn by Ellie Goulding.   Here’s a short, low-res excerpt, but I strongly suggest that you go and watch the full version here: Cannes Burn

Unlike all of the other hacks that I’ve built, this one feels really personal to me.  I wasn’t just trying to solve a technical problem. I was trying to capture the essence of the song in code, trying to tell its story and maybe even touch the viewer.  The challenge wasn’t in the coding it was in the feeling.

After every hack day, I’m usually feeling a little depressed.  I call it post-hacking depression. It is partially caused by being sleep deprived for 48 hours, but the biggest component is that I’ve put my all into something for 48 hours and then it is just over. The demo is done, the code is checked into github, the app is deployed online and people are visiting it (or not). The thing that just totally and completely took over my life for two days is completely gone. It is easy to reflect back on the weekend and wonder if all that time and energy was worth it.

Monday night after the MIDEM hack day was over I was in the midst of my post-hack depression sitting in a little pub called Le Crillon when a guy came up to me and said “I saw your hack.  It made me feel something. Your hack moved me.”

Cannes Burn won’t be my post popular hack, nor is it my most challenging hack, but it may be my favorite hack because I was able to write some code and make somebody that I didn’t know feel something.

 

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Cannes Burn

This weekend brought me to Cannes and the French Riviera for the MIDEM Music Hack Day where I’ve spent about 40 hours working on my music hack called Cannes Burn.  Cannes Burn is a visualization that accompanies the song Burn by Ellie Goulding. Go check it out if you haven’t already seen it before reading on. It requires a modern computer and browser that supports webgl.

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The Hack uses the new ENsync.js library that I created last week. ENsync uses the Echo Nest analysis to provide synchronization of a JS web app with music.  With ENsync you can setup elaborate animations that are triggered by musical events (such on every bar, beat or tatum).  The Hack also uses threejs – the amazing 3D library by Mr.Doob.

Creating the hack was a whole lot of fun – I spent hours building 3D shapes out of flying cubes. I probably listened to the song Burn many hundreds of times this weekend. (Thanks to my hacker neighbors who put up with my endless Ellie looping without complaint).  

It has been a great weekend here in Cannes. It is so inspiring to be surrounded by a bunch of really smart folks who are passionate about music and technology and see and hear how they are building their stuff.  Such a great, sharing vibe from all of the hackers. I feel really lucky to  part of it all!   

Check out all the hacks on hacker league:  MIDEM Music Hack Day Hacks and check out my hack at:  Cannes Burn

 

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New Genre APIs

localhost_8000_index.html-2Today at the Echo Nest we are pushing out an update to our Genre APIs. The new APIs lets you get all sorts of information about any of over 800 genres including a description of the genre,  representative artists in the genre, similar genres, and links to web resources for the genre (such as a wikipedia page, if one exists for a genre).  You can also use the genres to create various types of playlists.  With these APIs you build all sorts of music exploration apps like Every Noise At Once, Music Popcorn and Genre-A-Day.

The new APIs are quite simple to use. Here are a few python examples created using pyen.

List all of the available genres with a description

This outputs text like so:

We can get the top artists for any genre like so:

Here are the top artists for ‘cool jazz’

We can find similar genres to any genre with this bit of code:

Sample output:

% python sim_genres.py cool jazz
bebop
jazz
hard bop
contemporary post-bop
soul jazz
big band
jazz christmas
stride
jazz funk
jazz fusion
avant-garde jazz
free jazz

We can use the genres to create excellent genre playlists. To do so, create a playlist of type ‘genre-radio’ and give the genre name as a seed.  We’ve also added a new parameter called ‘genre_preset’ that, if specified will control the type of songs that will be added to the playlist. You can chose from core, in_rotation, and emerging. Core genre playlists are great for introducing a new listener to the genre.  Here’s a bit of code that generates a core playlist for any genre:

The core classic rock playlist looks like this:

  1. Simple Man by Lynyrd Skynyrd
  2. Born To Be Wild by Steppenwolf
  3. All Along The Watchtower by Jimi Hendrix
  4. Kashmir by Led Zeppelin
  5. Sunshine Of Your Love by Cream
  6. Let’s Work Together by Canned Heat
  7. Gimme Shelter by The Rolling Stones
  8. It’s My Life by The Animals
  9. 30 Days In The Hole by Humble Pie
  10. Midnight Rider by The Allman Brothers Band
  11. The Joker by Steve Miller Band
  12. Fortunate Son by Creedence Clearwater Revival
  13. Black Betty by Ram Jam
  14. Heart Full Of Soul by The Yardbirds
  15. Light My Fire by The Doors

The ‘in rotation’ classic rock playlist looks like this:

  1. Heaven on Earth by Boston
  2. Doom And Gloom by The Rolling Stones
  3. Little Black Submarines by The Black Keys
  4. I Gotsta Get Paid by ZZ Top
  5. Fly Like An Eagle by Steve Miller Band
  6. Blue On Black by Kenny Wayne Shepherd
  7. Driving Towards The Daylight by Joe Bonamassa
  8. When A Blind Man Cries by Deep Purple
  9. Over and Over (Live) by Joe Walsh
  10. The Best Is Yet To Come by Scorpions
  11. World Boss by Gov’t Mule
  12. One Way Out by The Allman Brothers Band
  13. Corned Beef City by Mark Knopfler
  14. Bleeding Heart by Jimi Hendrix
  15. My Sharona by The Knack

While the emerging ‘classic rock’ playlist looks like this:

  1.  If You Were in Love by Boston
  2.  Beggin’ by Shocking Blue
  3.  Speak Now by The Answer
  4.  Mystic Highway by John Fogerty
  5.  Hell Of A Season by The Black Keys
  6.  No Reward by Gov’t Mule
  7.  Pretty Wasted by Tito & Tarantula
  8.  The Battle Of Evermore by Page & Plant
  9.  I Got All You Need by Joe Bonamassa
  10.  What You Gonna Do About Me by Buddy Guy
  11.  I Used To Could by Mark Knopfler
  12. Wrecking Ball by Joe Walsh
  13. The Circle by Black Country Communion
  14. You Could Have Been a Lady by April Wine
  15. 15 Lonely by Walter Trout

The new Genre APIs are really quite fun to use. I’m looking forward to seeing a whole new world of music exploration and discovery apps built around these APIs.

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Must listen to podcast – Digital Music Trends

My top ‘must-listen’ podcast is now Andrea Leonelli’s Digital Music Trends.  This weekly podcast is jam packed with analysis and info about what’s going on in the digital music space.  The latest podcast includes Music Hack Day master Martyn Davies and Ben Graham from StrategyEye in a round table discussion on Gracenote’s recent sale, their Rhythm announcment, CES and more. Good stuff.

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Six Degrees of Black Sabbath (v2)

For my Christmas vacation programming project this year, I revisited an old hack: Six Degrees of Black Sabbath.  I wrote the original, way back in 2010 at the very first San Francisco Music Hack Day. That version is still up and running, and getting regular visits, but it is getting a bit long in the tooth and so I’ve given it  a total rewrite from the ground up. The result is the new Six Degrees of Black Sabbath:

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Six Degrees of Black Sabbath is like the Oracle of Bacon but for music. It lets you find connections to just about any two artists based upon their collaborations.   Type in the name of two artists, and 6dobs will give you a pathway showing the connections that will get you from one artist to another. For instance, if you enter ‘The Beatles’ and ‘Norah Jones’ you’ll get a path like:

If you don’t like a particular connection, you can bypass it generating a new path. For instance, if we bypass Ravi Shankar, it will take us eight steps to get to Norah Jones from the Beatles:

The Beatles -> Paul McCartney -> The Fireman -> Youth -> Pigface
-> Mike Dillon ->Garage A Trois -> Charlie Hunter -> Norah Jones

Not all connections are created equal.  Mick Jagger and Keith Richards have been playing together for over 50 years in the Rolling Stones. That’s a much stronger connection than the one between Mick Jagger and Fergie for performing a single song together at the Rock and Roll Hall of Fame.  We take these connection strengths into account when finding paths between artists. Preference is given to stronger connections, even if those stronger connections will yield a longer path.

The new version of Six Degrees of Black Sabbath has a number of new features:

Video – Each step in a path is represented by a Youtube video – often with a video by the two artists that represent that step. I’m quite pleased at how well the video works for establishing the connection between two artists. Youtube seems to have it all.
From_The_Monkees_to_Justin_Bieber_in_11_steps_

Live stats  – The app tracks and reports all sorts of things such as the longest path discovered so far, the most frequently occurring artists on paths, the most connected artists, most searched for artists and so on.

Larger database of connections – the database has about a quarter million artists and 2.5 million artist-to-artist connections.

Autocomplete for artist names – no need to try to remember how to spell ‘Britney Spears‘ – just start typing the parts you know and it will sort it out.

Spiffier looking UI –  It still looks like it was designed by an engineer, but at least it looks like it was designed in this decade by an engineer.

Path finding improvements – faster and better paths throughout.

Revisiting this app after 4 years was a lot of fun. I got to dive deep into a bunch of tech that was new to me including Redis, Bootstrap 3, and the YouTube video search API. I spent many hours untangling the various connections in the new Musicbrainz schema.  I took a tour through a number of Pythonic network graph libraries (Networkx, igraph and graph-tool), I learned a lot about Python garbage collection when you have a 2.5gb heap.

Give the app a try and let me know what you think.

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Million Song Shuffle

20111023_ipod_jpg__1337×1563_Back in 2001 when the first iPod was released, Shuffle Play was all the rage. Your iPod had your 1,000 favorite songs on it, so picking songs at random to play created a pretty good music listening experience. Today, however, we don’t have 1,000 songs in our pocket. With music services like Rdio, Rhapsody or Spotify, we are walking around with millions of songs in our pocket. I’ve often wondered what it would be like to use Shuffle Play when you have millions of songs to shuffle through. Would it be a totally horrible listening experience listening to artists that are so far down the long tail that they don’t even know that they are part of a dog? Would you suffer from terminal iPod whiplash as you are jerked between Japanese teen pop and a John Philip Sousa march?

To answer these questions, I built an app called Million Song Shuffle. This app will create a playlist by randomly selecting songs from a pool of many millions of songs. It draws from the Rdio collection and if you are an Rdio user you can hear listen to the full tracks.

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The app also takes advantage of a nifty new set of data returned by the Echo Nest API. It shows you the absolute hotttnesss rank for the song and the artist, so you will always know how deep you are into the long tail (answer: almost always, very deep).

So how is listening to millions of songs at random? Surprisingly, it’s not too bad. The playlist certainly gets a high score for eclecticism and surprise, and most of the time the music is quite listenable. But give it a try, and form your own opinion.

Its fun, too, to see how long you can listen to the Million Song Shuffle before you encounter a song or even an artist that you’ve heard of before. If the artist is not in the top 5K artists, it is likely you’ve never heard of them. After listening to Million Song Shuffle for a little while you start to get an idea of how much music there is out there. There’s a lot.

For the ultimate eclectic music listening experience, try the Million Song Shuffle.

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Have a Very Nestive Christmas

We are approaching peak Christmas music season. That means that many of us are getting really sick of hearing the same Christmas songs over and over.  One can only hear Bing Crosby’s White Christmas so many times before measures must be taken.  To remedy this situation,  this morning I created a quick web app that  let you chose from among a number of different Christmas genres (from classical to heavy metal) to let you add a little variety to your Christmas mix.  If you are getting weary of the Christmas standards, but still want to listen to Christmas music, you may want to give it a try:  The Christmas Playlister

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