Posts Tagged spotify
Every week, thousands of artists release albums on Spotify. Sifting through all this new music to find good stuff to listen to can be hard. Luckily, there are lots of tools from New Music Tuesday playlists to the Spotify Viral 50 to help us find the needles in the proverbial haystack of new music. However, most of these tools tend to surface up new music by artists that have been around for a while. For instance, the top artist on Spotify Viral 50 as I write this is Jeremih who has been on the charts for five years. The top of New Music Tuesday right now is Mumford & Sons who’ve been recording for at least eight years.
I’m interested in finding music by the freshest artists – artists that are at the very beginning of their recording careers. To that end, I’ve built a new chart called ‘The Fresh 40’ that shows the top albums by the freshest artists. To build The Fresh 40 I scour through all of the albums that have been released in the last two weeks on Spotify (on average that’s about 30 thousand albums), and find the albums that are the very first album release for its artist. I then rank each album by a weighted combination of the number of followers the artist has on Spotify and the popularity of the artist and album (which is related to Spotify track plays). The result is a chart of the top 40 most popular fresh artists.
The Fresh 40 updates every day and shows all the salient info including the rank, yesterday’s rank, the overall score, artist followers, artist popularity, album popularity and the number of days that the album has been on the chart. Since an album can only be on the chart for 15 days, there’s quite a bit of change from day to day.
If you are interested in finding music by the very newest artists on Spotify, you might be interested in The Fresh 40. Give the chart a look.
My weekend programming project this week was to explore a new feature of the Spotify Web API that allows you to find albums that have been released in the last two weeks. The result is a web app called Fresh Faces. This app goes through all of the recent releases and finds those that are the very first release for the artist. If you are looking for new music, there’s no fresher place to start than this app – it finds the newest music by the freshest artists – artists that are barely two weeks into their recording career.
Fresh Faces lets you sort the results based on artist popularity, album popularity, artist followers or release date. You can click on an album to hear a sample, find more info about the album or open it on Spotify.
How many new releases are there?
I was curious about how many releases there are in a two week period, and when releases tend to happen, so I added a chart at the bottom of the Fresh Faces app that shows the distribution of fresh and recurring releases and the dates when releases happen. You can see that the shift of releasing music from Tuesday to Friday is ongoing.
In the past two weeks about 32,000 albums have been released – about 5,200 of these are the first release for the artist. That’s a whole lot of fresh music.
Give Fresh Faces a try and let me know what you think.
One of the problems with working at a company like Spotify is that my Spotify account gets filled up with all sorts of work-related playlists. Over the last few years I’ve built lots of apps that create playlists. When I test these apps I end up generating lots of playlists that I will never ever listen to. If I were a tidy soul, I’d clean up my playlists after ever project, but, alas, that is something I never do. The result is that after working at Spotify for a year (and using Spotify for 8 years), I’ve accumulated many hundreds of garbage playlists. Now I could go into the Spotify desktop client and clean these up, but in the current client there’s no good way to bulk delete playlists. Each playlist delete takes at least 3 clicks. The prospect of doing this hundreds of times to clean up the playlist garbage is a bit overwhelming.
I had a few hours to kill in a coffeeshop yesterday so I decided to deal with my playlist mess. I wrote a little Spotify web app called The Unfollower that lets you unfollow any of your playlists with a single click. If you change your mind, you can re-follow any playlist that you unfollow.
The Unfollower uses the Spotify Web API to make it all happen. In particular it relies on the Follow/Unfollow API that was recently added by the API team.
If you are like me and have lots of dead playlists clogging up your Spotify, and you are looking for a streamlined way of cleaning them up, give The Unfollower a try.
Yesterday I gave a talk at SXSW about what we can learn about how we listen to music by looking at all sorts of listener data that we collect at Spotify. You can see the slides for my talk here … but the slides only tell half the story, the other have are in my words, but those aren’t written down anywhere. You’ll just have to assume that they were very insightful, and a little bit humorous, but at the end told an incredible story leaving you inspired and fulfilled.
The Spotify Insights team took a deep dive into some of the listening data of college students to see if there were any differences in how students at different schools listen. We looked at a wide range of data including what artists were played, what songs were played and when, what playlists played, what genres were played and so on. We focused mostly on looking for distinctive listening patterns and behaviors at the different schools. The results were a set of infographic style visualizations that summarize the distinctive listening patterns for each school.
It was a fun study to do and really shows how much we learn about listening behavior based upon music streaming behavior. Read about the study on the Spotify Insights Blog: Top 40 Musical Universities in America:How Students Listen
My Music Hack Day Berlin hack was “Where’s the Drama?” – a web app that automatically identifies the most dramatic moment in any song and plays it for you. I’ve been having lots of fun playing with it … and even though (or perhaps because) I know how it works, I’m often surprised at how well it does at finding the most dramatic moments. Here are some examples:
- When will the Bass Drop – Lonely Island
- Stairway to Heaven – Led Zeppelin
- Doomsday – Nero
- November Rain – Guns N Roses
How does it work? The app grabs the detailed audio analysis for the song from The Echo Nest. This includes a detailed loudness map of the song. This is the data I use to find the drama. To do so, I look for the part of the song with the largest rise in volume over the course of a 30 second window (longer songs can have a bit of a longer dramatic window). I give extra weight to crescendos that culminate in louder peaks (so if there are two crescendos that are 20dB in range but one ends at 5dB louder, it will win). Once I identify the most dynamic part of a song, I pad it a bit (so we get to hear a bit of the drop after the build).
Playing the music – I wanted to use Spotify to play the music, which was a bit problematic since there currently isn’t a way to play full streams with the Spotify Web API, so I did a couple of hacky hacks that got me pretty far. First of all, I discovered that you can add a time offset to a Spotify URI like so:
When this URI is opened in Spotify (even when opened via a browser), Spotify will start to play the song a the 1:05 time offset.
I still needed to be able to stop playing the track – and there’s no way to do that directly – so instead, I just open the URI:
which happens to be the URI for John Cage’s 4’33. In other words, to stop playing one track, I just start playing another (that happens to be silent). The awesome side effect of this is that I’ll be slowly turning anyone who uses “Where’s the Drama?” into experimental music listeners as the Spotify recommendation system responds to all of those John Cage ‘plays’. This should win some sort of ‘hackiest hack of the year’ award.
It was a fun hack to make, and great fun to demo. And now that I have the app, I am no longer wasting time listening to song intros and outros, I can just get to the bit of the song that matters the most.
On the very same day that Spotify announced its acquisition of The Echo Nest they released a brand new Spotify iOS SDK. Trying this new SDK out has been high on my priority list, and finally after a few crazy weeks I’ve had a bit of time to take it for a test drive. I walked through the beginner’s tutorial and was up and running with an iOS app running in the simulator in about 30 minutes. Easy Peazy! The bit that took the longest was setting up the token exchange service. This is a service that you need to run on your own server as part of the authentication process. The tutorial provides such a sample service written in ruby, however I’m not a ruby programmer so I had to go through all the gyrations of installing ruby, figuring out how to install gems and getting the required gems installed. Once I had everything installed it worked fine and I was able to get the tutorial running. However, I figure that I’ll be working with the iOS SDK a great deal in my future, and I’d rather not have to deal with a ruby server every time I create a new app, and so for my Sunday morning programming project I’ve re-written the ruby swap service in python. The service is on github here: spotify_token_swap
If you are going to be using the new Spotify iOS SDK to create apps and you’d rather deal with python than ruby, then you might find it useful.
I love writing music apps and playing with music data. How much? Every weekend I wake up at 6am and spend a long morning writing a new music app or playing with music data. That’s after a work week at The Echo Nest, where I spend much of my time writing music apps and playing with music data. The holiday break is even more fun, because I get to spend a whole week working on a longer project like Six Degrees of Black Sabbath or the 3D Music Maze.
That’s why I love working for The Echo Nest. We have built an amazing open API, which anyone can use, for free, to create music apps. With this API, you can create phenomenal music discovery apps like Boil the Frog that take you on a journey between any two artists, or Music Popcorn, which guides you through hundreds of music genres, from the arcane to the mainstream. It also powers apps that create new music, like Girl Talk in a Box, which lets you play with your favorite song in the browser, or The Swinger, which creates a Swing version of any song:
One of my roles at The Echo Nest is to be the developer evangelist for our API — to teach developers what our API can do, and get them excited about building things with it. This is the best job ever. I get to go to all parts of the world to attend events like Music Hack Day and show a new crop of developers what they can do with The Echo Nest API. In that regard, it’s also the easiest job ever, because when I show apps that developers have built with The Echo Nest API, like The Bonhamizer and The Infinite Jukebox, or show how to create a Pandora-like radio experience with just a few lines of Python, developers can’t help but get excited about our API.
At The Echo Nest we’ve built what I think is the best, most complete music API — and now our API is about to get so much better.
Today, we’ve announced that The Echo Nest has been acquired by Spotify, the award-winning digital music service. As part of Spotify, The Echo Nest will use our deep understanding of music to give Spotify listeners the best possible personalized music listening experience.
Spotify has long been committed to fostering a music app developer ecosystem. They have a number of APIs for creating apps on the web, on mobile devices, and within the Spotify application. They’ve been a sponsor and active participant in Music Hack Days for years now. Developers love Spotify, because it makes it easy to add music to an app without any licensing fuss. It has an incredibly huge music catalog that is available in countries around the world.
Spotify and The Echo Nest APIs already work well together. The Echo Nest already knows Spotify’s music catalog. All of our artist, song, and playlisting APIs can return Spotify IDs, making it easy to build a smart app that plays music from Spotify. Developers have been building Spotify / Echo Nest apps for years. If you go to a Music Hack Day, one of the most common phrases you’ll hear is, “This Spotify app uses The Echo Nest API”.
I am incredibly excited about becoming part of Spotify, especially because of what it means for The Echo Nest API. First, to be clear, The Echo Nest API isn’t going to go away. We are committed to continuing to support our open API. Second, although we haven’t sorted through all the details, you can imagine that there’s a whole lot of data that Spotify has that we can potentially use to enhance our API. Perhaps the first visible change you’ll see in The Echo Nest API as a result of our becoming part of Spotify is that we will be able to keep our view of the Spotify ID space in our Project Rosetta Stone ID mapping layer incredibly fresh. No more lag between when an item appears in Spotify and when its ID appears in The Echo Nest.
The Echo Nest and the Spotify APIs are complementary. Spotify’s API provides everything a developer needs to play music and facilitate interaction with the listener, while The Echo Nest provides deep data on the music itself — what it sounds like, what people are saying about it, similar music its fans should listen to, and too much more to mention here. These two APIs together provide everything you need to create just about any music app you can think of.
I am a longtime fan of Spotify. I’ve been following them now for over seven years. I first blogged about Spotify way back in January of 2007 while they were still in stealth mode. I blogged about the Spotify haircuts, and their serious demeanor:
Last month, on a very cold and snowy day in Boston, I sat across a conference table from of bunch of really smart folks with Swedish accents. As they described their vision of a music platform, it became clear to me that they share the same obsession that we do with trying to find the best way to bring fans and music together.
Together, we can create the best music listening experience in history.
I’m totally excited to be working for Spotify now. Still, as with any new beginning, there’s an ending as well. We’ve worked hard, for many years, to build The Echo Nest — and as anyone who’s spent time here knows, we have a very special culture of people totally obsessed with building the best music platform. Of course this will continue, but as we become part of Spotify things will necessarily change, and the time when The Echo Nest was a scrappy music startup when no one in their right mind wanted to be a music startup will be just a sweet memory. To me, this is a bit like graduation day in high school — it is exciting to be moving on to bigger things, but also sad to say goodbye to that crazy time in life.
There is a big difference: When I graduated from high school and went off to college, I had to say goodbye to all my friends, but now as I go off to the college of Spotify, all my friends and classmates from high school are coming with me. How exciting is that!
Spotify just released a nifty embeddable play button. With the play button you can easily embed Spotify tracks in any web page or blog. Since there’s really tight integration between the Spotify and Echo Nest IDs, I thought I’d make a quick demo that shows how we can use the Echo Nest playlist API and the new Spotify Play button to make playlists.
The demo took about 5 minutes to write (shorter than it is taking to write the blog post). It is simple artist radio on a web page. Give it a go at: Echo Nest + Spotify Play Button Demo
Here’s what it looks like.
Update: Charlie and Samuel pointed out that there is a multi-track player too. I made a demo that uses that too:
The Spotify Play button is really easy to use, looks great. Well done Spotify.
With the recently announced Spotify integration into Rosetta Stone, The Echo Nest now makes available a detailed audio analysis for millions of Spotify tracks. This audio analysis includes summary features such as tempo, loudness, energy, danceability, key and mode, as well as a set of fine-grained segment features that describe details such as where each bar, beat and tatum fall and the detailed pitch, timbral and loudness content of each audio event in the song. These features can be very useful for driving Spotify applications that need to react to what the music sounds like – from advanced dynamic music visualizations like the MIDEM music machine or synchronized music games like Guitar Hero.
I put together a little Spotify App that demonstrates how to synchronize Spotify Playback with the Echo Nest analysis. There’s a short video here of the synchronization:
video on youtube: http://youtu.be/TqhZ2x86RXs
In this video you can see the audio summary for the currently playing song, as well as a display synchronized ‘bar’ and ‘beat’ labels and detailed loudness, timbre and pitch values for the current segment.
How it works:
To get the detailed audio analysis, call the track/profile API with the Spotify Track ID for the track of interest. For example, here’s how to get the track for Radiohead’s Karma Police using the Spotify track ID:
This returns audio summary info for the track, including the tempo, energy and danceability. It also includes a field called the analysis_url which contains an expiring URL to the detailed analysis data. (A very abbreviated excerpt of an analysis is contained in this gist).
To synchronize Spotify playback with the Echo Nest analysis we need to first get the detailed analysis for the now playing track. We can do this by calling the aforementioned track/profile call to get the analysis_url for the detailed analysis, and then retrieve the analysis (it is stored in JSON format, so no reformatting is necessary). There is one technical glitch though. There is no way to make a JSONP call to retrieve the analysis. This prevents you from retrieving the analysis directly into a web app or a Spotify app. To get around this issue, I built a little proxy at labs.echonest.com that supports a JSONP style call to retrieve the contents of the analysis URL. For example, the call:
will return the analysis json wrapped in the foo() callback function. The Echo Nest does plan to add JSONP support to retrieving analysis data, but until then feel free to use my proxy. No guarantees on support or uptime since it is not supported by engineering. Use at your own risk.
Once you have retrieved the analysis you can get the current bar, beat, tatum and segment info based upon the current track position, which you can retrieve from Spotify with: sp.getTrackPlayer().getNowPlayingTrack().position. Since all the events in the analysis are timestamped, it is straightforward to find a corresponding bar,beat, tatum and segment given any song timestamp. I’ve posted a bit of code on gist that shows how I pull out the current bar, beat and segment based on the current track position along with some code that shows how to retrieve the analysis data from the Echo Nest. Feel free to use the code to build your own synchronized Echo Nest/Spotify app.
The Spotify App platform is an awesome platform for building music apps. Now, with the ability to use Echo Nest analysis from within Spotify apps, it is a lot easier to build Spotify apps that synchronize to the music. This opens the door to a whole range of new apps. I’m really looking forward to seeing what developers will build on top of this combined Echo Nest and Spotify platform.