The Playlist Survey

Posted by Paul in events, Music, playlist, recommendation, research on June 18, 2010

[tweetmeme source= ‘plamere’ only_single=false] Playlists have long been a big part of the music experience.  But making a good playlist is not always easy.  We can spend lots of time crafting the perfect mix, but more often than not, in this iPod age, we are likely to toss on a pre-made playlist (such as an album),  have the computer generate a playlist (with something like iTunes Genius) or (more likely) we’ll just hit the shuffle button and listen to songs at random.   I pine for the old days when Radio DJs would play well-crafted sets – mixes of old favorites and the newest, undiscovered tracks – connected in interesting ways.  These professionally created playlists magnified the listening experience.   The whole was indeed greater than the sum of its parts.

The tradition of the old-style Radio DJ continues on Internet Radio sites like Radio Paradise. RP founder/DJ Bill Goldsmith says of   Radio Paradise: “Our specialty is taking a diverse assortment of songs and making them flow together in a way that makes sense harmonically, rhythmically, and lyrically — an art that, to us, is the very essence of radio.”  Anyone who has listened to Radio Paradise will come to appreciate the immense value that a professionally curated playlist brings to the listening experience.

I wish I could put Bill Goldsmith in my iPod and have him craft personalized playlists for me  – playlists that make sense harmonically, rhythmically and lyrically, and customized to my music taste,  mood and context . That, of course, will never happen. Instead I’m going to rely on computer algorithms to generate my playlists.  But how good are computer generated playlists? Can a computer really generate playlists as good as Bill Goldsmith,  with his decades of knowledge about good music and his understanding of how to fit songs together?

To help answer this question,  I’ve created a Playlist Survey – that will collect information about the quality of playlists generated by a human expert, a computer algorithm and a random number generator.   The survey presents a set of playlists and the subject rates each playlist in terms of its quality and also tries to guess whether the playlist was created by a human expert, a computer algorithm or was generated at random.

Bill Goldsmith and Radio Paradise have graciously contributed 18 months of historical playlist data from Radio Paradise to serve as the expert playlist data. That’s nearly 50,000 playlists and a quarter million song plays spread over nearly 7,000 different tracks.

The Playlist Survey also servers as a Radio DJ Turing test.  Can a computer algorithm (or a random number generator for that matter) create playlists that people will think are created by a living and breathing music expert?  What will it mean, for instance, if we learn that people really can’t tell the difference between expert playlists and shuffle play?

Ben Fields and I will offer the results of this Playlist when we present Finding a path through the Jukebox – The Playlist Tutorial – at ISMIR 2010 in Utrecth in August. I’ll also follow up with detailed posts about the results here in this blog after the conference.  I invite all of my readers to spend 10 to 15 minutes to take The Playlist Survey.  Your efforts will help researchers better understand what makes a good playlist.

Take the Playlist Survey

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MeToo – a scrobbler for the room

Posted by Paul in code, fun, Music, The Echo Nest, web services on June 11, 2010

[tweetmeme source= ‘plamere’ only_single=false] One of the many cool things about working at the Echo Nest is that we have  an Sonos audio system with  single group playlist for the office. Anyone from the CEO to the greenest intern can add music to the listening queue for everyone to listen to. The office, as a whole has a rather diverse taste in music and as a result I’ve been exposed to lots of interesting music.   However, the downside of this is that since I’m not listening to music being played on my personal computer, every day I have 10 hours of music listening that is never scrobbled, and as they say, if it doesn’t scrobble, it doesn’t count.   Sure the Sonos system scrobbles all of the plays  to the Echo Nest account on Last.fm but I’d also like it to scrobble it to my account so I can use nifty apps like  Lee Byron’s Last.fm Listening History or  Matt Ogle’s Bragging Rights on my own scrobbles.

This morning while listening to that nifty Emeralds album,  I decided that I’d deal with those scrobble gaps once and for all.  So I wrote a little python script called MeToo that keeps my scrobbles up to date.  It’s really quite simple. Whenever I’m in the office, I fire up MeToo.  MeToo watches the most recent tracks played on The Echo Nest account and whenever a new track is played, it scrobbles it to my personal account. In effect, my scrobbles will track the office scrobbles.  When I’m not listening I just close my laptop and the scrobbling stops.

The script itself is pretty simple – I used pylast to do interfacing to Last.fm –  the bulk of the logic is less than 20 lines of code.   I start the script like so:

% python metoo.py TheEchoNest lamere

when I do that, MeToo will continuously monitor most recently played tracks on TheEchoNest and scrobble the plays on my account. When I close my laptop, the script is naturally suspended – so even though music may continue to play in the office, my laptop won’t scrobble it.

My scrobbles and Echo Nest scrobbles

I suspect that this use case is relatively rare, and so there’s probably not a big demand for something like MeToo, but if you are interested in it, leave a comment. If I see some interest, I’ll toss it up on google code so anyone can use it.

It feels great to be scrobbling again!

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We swing both ways

Posted by Paul in code, fun, Music, remix, The Echo Nest on June 7, 2010

Perhaps one of the most frequently asked questions about Tristan’s Swinger is whether it can be used to ‘Un-swing’ a song.  Can you take a song that already swings and straighten it out? Indeed, the answer is yes – we can swing both ways  – but it is harder to unswing than it is to swing.  Ammon on Happy Blog, the Happy Blog has given de-swinging a go with some success with his de-swinging of Revolution #1.   Read his post and have a listen at Taking the swing out of songs.   I can’t wait for the day when we can turn on the TV to watch and listen to  MTV-Unswung.

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Frasier does Nine Inch Nails

Posted by Paul in code, fun, remix, The Echo Nest on June 5, 2010

Oh My –  Musician Josh Millard  has recreated The Downward Spiral using nothing but audio from the NBC sitcom Frasier. So wrong, and yet, so right.  Josh has the whole remixed album plus a video on his blog:

Nine Inch Niles – The Seattleward Spiral

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Is Music Recommendation Broken? How can we fix it?

Posted by Paul in events, Music, recommendation, research on June 1, 2010

Save the date: 26th September 2010 for The Workshop on Music Recommendation and Discovery being held in conjunction with ACM RecSys in Barcelona, Spain.  At this  workshop, community members from the Recommender System, Music Information Retrieval, User Modeling, Music Cognition, and Music Psychology can meet, exchange ideas and collaborate.

Topics of interest

Topics of interest for Womrad 2010 include:

  • Music recommendation algorithms
  • Theoretical aspects of music recommender systems
  • User modeling in music recommender systems
  • Similarity Measures, and how to combine them
  • Novel paradigms of music recommender systems
  • Social tagging in music recommendation and discovery
  • Social networks in music recommender systems
  • Novelty, familiarity and serendipity in music recommendation and discovery
  • Exploration and discovery in large music collections
  • Evaluation of music recommender systems
  • Evaluation of different sources of data/APIs for music recommendation and exploration
  • Context-aware, mobile, and geolocation in music recommendation and discovery
  • Case studies of music recommender system implementations
  • User studies
  • Innovative music recommendation applications
  • Interfaces for music recommendation and discovery systems
  • Scalability issues and solutions
  • Semantic Web, Linking Open Data and Open Web Services for music recommendation and discovery

More info:  Wormrad 2010 Call for papers

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What is the longest path though Six Degrees of Black Sabbath?

Posted by Paul in events, fun, Music, The Echo Nest on May 25, 2010

[tweetmeme source= ‘plamere’ only_single=false] @meekles tweeted yesterday that he had found a 25 step path through Six Degrees of Black Sabbath and challenged anyone to find a longer path that his Path from Arthur to Eivind Fjoseide.

To sweeten the challenge, I’ll offer a prize of a coveted Echo Nest Tee Shirt for each new longest path found.  Here are the rules:

  • When you find a path that you think is longer than any found so far, tweet the path with its length and the hashtags #6dobs and #longest. For example:  I made a 25 step path from arthur to Eivind Fjoseide #6dobs #longest http://bit.ly/9DANCk
  • No skipping allowed in longest paths
  • Only one tee-shirt given per milestone – so if 5 people find a 27 step path, only the first who finds it gets the tee-shirt
  • Only one tee-shirt per person
  • You are not eligible if you work for the Echo Nest, or if your name is Kurt Jacobson

The Echo Nest tee-shirt will turn you into a music metadata superhero

Have fun finding those paths!

Six Degrees of Black Sabbath

Update: Great work finding paths of at least 40 artists long.  Tee-shirt give away ends tonight (May 25) at midnight EDT!

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Sweet Child O’Mine – Vienna Style

Posted by Paul in Music, remix, research, The Echo Nest on May 24, 2010

I was wondering how far one could go with the time-stretching stuff and still make something musical.  Here’s an attempt to turn a rock anthem into a waltz.  It is a bit rough in a few places, especially the beginning – but  I think it settles into a pretty nice groove.

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The Swinger

Posted by Paul in Music, remix, The Echo Nest on May 21, 2010

[tweetmeme source= ‘plamere’ only_single=false] One of my favorite hacks at last weekend’s Music Hack Day is Tristan’s Swinger.  The Swinger is a bit of python code that takes any song and makes it swing.  It does this be taking each beat and time-stretching the first half of each beat while time-shrinking the second half.  It has quite a magical effect.  Some examples:

Every Breath You Take

Money for Nothing

Cream

I Will

Update – a few more tracks -by request:

Enter Sandman

Daft Punk’s Around the world

Sweet Child O’ Mine

(one of my favs)

Don’t Stop Believin’

White Rabbit

(this one is hypnotic)

Swinger uses the new Dirac time-stretching capabilities of Echo Nest remix. Source code is available in the samples directory of remix.

Be sure  to check out some of the other Music Hack Day hacks like Six Degrees of Black Sabbath, Jason’s Songbird Visualizer or the Artikulator.

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Six Degrees of Black Sabbath

Posted by Paul in code, data, events, fun, Music, The Echo Nest on May 20, 2010

[tweetmeme source= ‘plamere’ only_single=false] My hack at last week’s Music Hack Day San Francisco was Six Degrees of Black Sabbath – a web app that lets you find connections between artists based on a wide range of artist relations.  It is like The Oracle of Bacon  for music.

To make the connections between the artists I rely on the relation data from MusicBrainz.  MusicBrainz has lots of deep data about how various artists are connected.    For instance there are about 130,000 artist-to-artist connections – connections such as:

  • member of band
  • is person
  • personal relationship
  • parent
  • sibling
  • married
  • involved with
  • collaboration
  • supporting musician
  • vocal supporting musician
  • instrumental supporting musician
  • catalogued

So from this data we know that George Harrison and Paul McCartney are related because each was a ‘member of the band’  of The Beatles.   In addition to the artist-to-artist data MusicBrainz has artist-track relations (Eric Clapton played on ‘While My Guitar Gently Weeps’),  artist-album (Brian Eno produced U2’s Joshua Tree),  track-track (Girl Talk samples ‘Rock You Like A Hurricane’ by the Scorpions for the track ‘Girl Talk Is Here’).  All told there are about 130 different types of relations that can connect two artists.

Not all of these relationships are equally important.  Two artists that are members of the same band have a much stronger relationship than an artist that covers another artist.  To accommodate this I assign weights to the various different types of relationships – this was perhaps the most tedious and subjective part of building this app.

Once I have all the different types of relations I created a directed graph connecting all of the artists based upon these weighted relationships.   The resulting graph has 220K artists connected by over a million edges. Finding a path between a pair of artists  is a simple matter of finding the shortest weighted path through the graph.

We can learn a little bit about music by looking at some of the properties of the graph.   First of all,  the average distance in the graph between any two artists in the graph chosen at random is 7.  Some of the top most connected artists along with the number of connections:

Here we see some of the anomalies in the connection data  – any classical performer who performs a piece by Mozart is connected to Mozart – thus the high connectivity counts for classical composers.   A more interesting metric is the ‘betweeness centrality’ –  artists that occur on many shortest paths between other artists have higher betweenness than those that do not.   Artists with high betweenness centrality are the connecting fibers of the music space.  Here are the top connecting artists:

I had never heard of Pigface before I started this project – and was doubtful that they could really be such a connecting node in the world of music – but a look a their wikipedia page makes it instantly clear why they are such a central node – they’ve had well over a hundred members in the band over their history.     Black Sabbath, while not at the top of the list is still extremely well connected.

I wrote the app in python, relying on networkx for the graph building and path finding.  The system performs well, even surviving an appearance on the front page of Reddit.  It was a fun app to write – and I enjoy seeing all the interesting pathways people have found through the artist space.

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Earworm and Capsule at Music Hack Day San Francisco

Posted by Paul in events, Music, remix, The Echo Nest, web services on May 14, 2010

[tweetmeme source= ‘plamere’ only_single=false] This weekend The Echo Nest is releasing some new remix functionality – Earworm and Capsule.  Earworm lets you create a new version of a song that is any length you want.  Would you like 2 minute version of Stairway to Heaven? Or a 3 hour version of Freebird? Or an Infinitely long version of Sex Machine?  Earworm can do that.   Here’s a 60 minute version of a little Rolling Stones ditty:

Capsule takes a list of tracks and optimizes the song transitions by reordering them and applying automatic beat matching and cross fading to give you a seamless playlist.  It is really neat stuff.    Here’s an example of a capsule between two Bob Marley songs:

It makes a nice little Bob Marley medley.

Jason writes about Capsule and Earworm and some other new features in remix  in his new (and rather awesome) blog:  Running With Data – Earworm and Capsule.  Check it out.

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