Masters of Media » Music visualizations as a means for discovery
Posted by Paul in Music, visualization on April 15, 2011
Nifty blog post by Megan Adams about using music visualization as a means for discovery:
Masters of Media » Music visualizations as a means for discovery.
Megan points to this thread on Tufte’s BBS about Reebee Garofalo’s ‘Genealogy of Pop/Rock Music”:
The comments in the BBS thread point to a number of visualizations that I hadn’t seen before including: this book on Rock Family Trees along with this incredibly detailed view of the Liverpool music scene.
MTV O Music Awards
Jennie with the SongKick prize
This is pretty cool – the hack that my daughter and I built at last fall’s Music Hack Day Boston was nominated for the Best Music Hack in the newly announced MTV O Music Awards – Online, Open, Ongoing Music Awards. Here are more details about the hack: Jennie’s Ultimate Road Trip, which includes this picture of Jennie playing the SongKick Ukelele. Seem’s like Jennie’s secret strategy to meet the Bieber might have some legs.
Other great music hacks were nominated too including the legendary Tim Soo’s Invisible Instruments and Marshall Jones’ Highlight to Listen. You can vote for your favorite music hack.
It is great to see Music Hacks included in a list of music awards. Thanks MTV!
9 reasons why Google and Apple should be worried
Posted by Paul in Music, recommendation on April 4, 2011
For the last year we’ve heard rumors of how both Apple and Google were getting close to releasing music locker services that allow music listeners to upload their music collection to the cloud giving them the ability to listen to their music everywhere. So it was a big surprise when the first major Internet player to launch a music locker service wasn’t Google or Apple, but instead was Amazon. Last week, with little fanfare, Amazon released its Amazon Cloud Drive, a cloud-based music locker that includes the Amazon Cloud Player allowing people to listen to their music anywhere. Amazon’s entry into the music locker is a big deal and should be particularly worrisome for Google and Apple. Amazon brings some special sauce to the music locker world that will make them a formidable competitor:
- Amazon can keep a secret – For the last year, we’ve heard much about the rumored Google and Apple locker services, but not a peep about the Amazon service. The first time people heard about the Amazon Locker service was when Amazon announced it on its front page. It says a lot about a large organization that can launch a major new product without rumors circulating in the industry.
- Amazon isn’t afraid to say “F*ck You” to the labels. While Apple and Google are negotiating licensing rights for the locker service, Amazon just went ahead and released their locker without any special music license. Amazon Director of Music Craig Pape told Billboard.biz “We don’t believe we need licenses to store the customers’ files. We look at it the same way as if someone bought an external hard drive and copy files on there for backup.”
- Amazon knows how to do the ‘cloud thing’ – Amazon has been leading the pack in cloud computing for years. They know how to build reliable, cost-effective cloud-based solutions, they’ve been doing it longer than anyone. Thousands of applications have been deployed in the Amazon cloud from big corporations to successful startups like dropbox. Compare to Apple’s track record for MobileMe. Of course Google knows how to do this stuff too, but they haven’t been immune to problems.
- Amazon knows about discovery – Amazon’s focus on discovery makes them a much better online bookstore than any other bookstore. They use all sorts of ways to connect a reader with a book. Collaborative filtering, book reviews, customer lists, content search, best seller lists , special deals. These techniques help get their readers deep into the long tail of books. Discovery is in Amazon’s genes. Contrast that to how Youtube helps you find videos, or how well Apple’s Genius helps you find music. Currently Amazon is providing no discovery tools yet with the Amazon Cloud Music Player, but you can bet that they will be adding these features soon.
- Amazon understands the importance of metadata – Amazon has always placed a premium on collecting high quality metadata about their media. That’s why they bought IMDB, and created SoundUnwound. That’s why when I uploaded 700 albums to the Amazon cloud, Amazon found album art and metadata for every single one of them. Compare that to iTunes which after nearly 10 years, still can’t seem to find album art for 90% of my music collection.
- Amazon does APIs – this is what I’m most excited about. Imagine if and when Amazon releases the Amazon Cloud Music API that lets a developer build applications around the content stored in a music locker. This will open the door for a myriad of applications from music visualizers, playlisting engines, event recommenders, and taste sharing, on our phones, on our set top boxes, on our computers.. Amazon has lead the way in making everything they do available via APIs. When they release the Amazon Cloud Music API, I think we’ll see a new level of creativity around music exploration, discovery, organization and listening.
- Amazon has done this before – The Kindle platform has already allowed you to do for books what the Amazon music locker does for music. You can buy content in the Amazon store, keep it in your locker and consume it on any device. This is not new tech for Amazon, they’ve been doing this for years already.
- Amazon has lots of customers – Last month Steve said he thought that Apple had more customer accounts than Amazon. Of course that was just a guess and Steve is not impartial. Amazon doesn’t say how many customer accounts they have, but we know its a lot. Amazon is clever in how they use the Music Locker to promote music purchases. Music you purchase from Amazon is stored for free in your locker, and when you buy an album your locker storage gets upgraded to 20GB for free.
- Amazon seems to care – Google has accidentally built the largest music destination on the Internet, but try to use YouTube to as a place to go and find music and you are faced with the challenge of separating the good music from the many covers, remixes, parodies and just plain crap that seem to fill the channel. iTunes has gone from a pretty good way to play music to becoming something that I only use to sync new content to my phone. It is bloated, slow and painful to use. In the ten years that Apple has been king of the digital music hill they’ve done little to help improve the music listening experience. Apple has moved on to video and Apps. Music is just another feature. Contrast that with what Amazon has done with the Kindle – they’ve made a device that arguably improves the reading experience. They chose eInk over color display, they keep the non-reading features to a minimum, they give a reader great discovery tools like the ability to sample the first few chapters of any book. I’m hopeful that Amazon will apply their same since of care for books to the world of music.
Amazon’s music locker is not perfect by any means. There’s no iPhone app. The storage is too expensive, there are no discovery or automatic playlisting features in the player. But what they’ve built is solid and usable. I’m also not bullish on music lockers. I’d rather pay $10 bucks a month to listen to any of 5 million tracks than to buy tracks at a dollar each. But I’m glad to see Amazon position itself so aggressively in this space. The competition between Google, Apple and Amazon will lead to a better music experience for us all.
Finding an artist’s peak year
Posted by Paul in Music, The Echo Nest on April 1, 2011
Many people have asked us here at the Echo Nest if, given our extensive musical data intelligence, we could potentially predict what artists will be popular in the future. While we believe that this is certainly within our capabilities, we see it as the final step in a long process.
So what’s the first step? To properly predict the future, we must first fully understand the past. To understand what artists will peak in the future, we must first figure out when current or past artists have peaked. Today marks the completion of this first step, culminating in the release of our artist/peak API:
http://developer.echonest.com/api/v4/artist/peak?name=The+Beatles&api_key=N6E4NIOVYMTHNDM8J
With this call you can see that the Beatles’s Peak year would have been 1977.
Given an artist, we will return the specific year in which they peaked:
- In most cases, though, the peak year will occur within the artist’s active years.
- In some cases, the year is prior to their active years, which we interpret as meaning that they were simply “late to the party”
- In other cases, the year is after their active years, which we interpret as meaning that these artists were ahead of their time, and that they ended their career too early.
With this new API call we can find out all sorts of things about music. Bieber peaked before he joined a label, The Beatles, Nirvana and Hendrix all stopped performing too soon, Metallica’s zenith was the Black Album, and Van Halen peaked after David Lee Roth left the band.
Join us in exploring the first concrete step in predictive analysis of popular music. If we’ve piqued your curiosity, take a peek at the peak method.
Shoutout to Mark Stoughton, chief of Q/A at The Echo Nest for architecting this find addition to our API.
Update – this API method is only available on April 1.
Finding Music With Pictures – The Video
Posted by Paul in events, Music, visualization on March 28, 2011
I gave a panel at SXSWi this year on using data visualization for music discovery. Mike Hochanadel made a video of the talk and has posted it online.
Be sure to check out the rest of Mike’s blog hoketronics – he has solid coverage on many of the SXSWi panels.
Memento Friday
It had to be done. Created with Echo Nest Remix.
Create an autocompleting artist suggest interface
Posted by Paul in code, Music, The Echo Nest on March 17, 2011
At The Echo Nest, we just rolled out the beta version of a new API method: artist/suggest – that lets you build autocomplete interfaces for artists. I wrote a little artist suggestion demo to show how to use the artist/suggest to build an autocomplete interface with jQuery.
The artist/suggest API tries to do the right thing when suggesting artist names. It presents matching artists in order of artist familiarity:
It deals with stop words (like the, and, and a) properly. You don’t need to type ‘the bea’ if you are looking for The Beatles but you can if you want to.
It deals with international characters in the expected way, so that we poor Americans that don’t know how to type umlauts can still listen to Björk:
The artist/suggest API is backed by millions of artists, including many, many artists that you’ve never heard of:
Integrating with jQuery is straightforward using the jQuery UI Autocomplete widget. The core code is:
$(function() {
$("#artist" ).autocomplete({
source: function( request, response ) {
$.ajax({
url: "http://developer.echonest.com/api/v4/artist/suggest",
dataType: "jsonp",
data: {
results: 12,
api_key: "YOUR_API_KEY",
format:"jsonp",
name:request.term
},
success: function( data ) {
response( $.map( data.response.artists, function(item) {
return {
label: item.name,
value: item.name,
id: item.id
}
}));
}
});
},
minLength: 3,
select: function( event, ui ) {
$("#log").empty();
$("#log").append(ui.item ? ui.item.id + ' ' + ui.item.label : '(nothing)');
},
});
});
The full code is here: http://static.echonest.com/samples/suggest/ArtistSuggestAutoComplete.html
A source function is defined that makes the jsonp call to the artist/suggest interface, and the response handler gets the extracts the matching artist names and ids from the result and puts them in a dictionary for use by the widget. Since the artist/suggest API also returns Echo Nest Artist IDs it is straightforward to turn make further Echo Nest calls to get detailed data for the artists. (Note that the artist/suggest API doesn’t allow you to specify buckets to add more data to the response like many of our other artist calls. This is so that we can keep the response time of the suggest API as low as possible for interactive applications).
We hope people will find the artist/suggest API. We are releasing it as a beta API – we may change how it works as we get a better understanding of how people want to use it. Feel free to send us any suggestions you may have.
Finding music with pictures: Data visualization for discovery
Posted by Paul in data, Music, visualization on March 13, 2011
I just finished giving my talk at SXSW called – ‘Finding Music with Pictures”. A few people asked for the slides – I’ve posted them to Slideshare. Of course all the audio and video is gone, but you can follow the links to see the vids. Here are the slides:
Lots of good tweets from the audience. And Hugh Garry has Storify’d the talk.
The Festival Explorer – Austin Edition
Posted by Paul in The Echo Nest on March 11, 2011
Looking for a tool to help you find the best bands to see in Austin during SXSW? Check out the Festival Explorer – Austin Edition:
It uses Echo Nest data like hotttness, top terms, similar artists to give you all sorts of ways to explore the over 2,000 artists playing in Austin during the next week. The Festival Explorer is a free iPhone app, available in the app store now: Festival Explorer Austin Edition
The SXSW Music Maze
Posted by Paul in code, fun, visualization on March 10, 2011
There are thousands of artists playing at SXSW this year. To help sort it all out, I thought I’d adapt my Music Maze to work within the world of SXSW 2011 artists. It is a good way to figure out which bands you’d like to see.
This visualization fits in with the SXSW talk I’m giving in a few days: Finding Music With Pictures
Music Machinery 
