Do you have a new, cool music app?
Do you have a new, cool music app? Consider entering it into the SXSW Accelerator at SXSW Music. This accelerator is for applications and technologies specifically designed for the use of musicians and the music business. These companies seek to advance the creation, distribution and promotion of recorded music, to facilitate licensing and payment for use of recordings, or to aid in the booking, logistics and promotion of live performances.
SXSW offers these to 10 reasons to enter your application into the SXSW Accelerator:
1. Expand Your Audience
Thousands of individuals from around the world flock to SXSW each year looking for the next big thing, and SXSW Accelerator is a major part of the excitement. Showcasing your idea at Accelerator is an incredible opportunity to get in front of individuals who can help take your concept to the next level.
2. Network with Industry Leaders
One of the greatest values of SXSW is the amazing mix of industry leaders, technology innovators, big-name companies, fresh startups, and independent talent attracted to the event. The ample socializing opportunities at SXSW Accelerator make it easy for participants to meet, greet, and establish a network of professionals to work with on current and future projects.
3. Refine Your Product
No matter how strong your pitch, to attract investors you need a strong product. Presenting your idea to an experienced panel of industry experts, and discussing your product with other entrepreneurs can help you to take it to the next level.
4. Polish Your Elevator Pitch
Pitching is the single-most important skill you need to rise above the competition. That pitch should be rock solid. At Accelerator, you get to pitch your nascent technologies to scores of innovators, content producers, media experts, and venture capitalists. Their feedback and expertise can help you sharpen that all-important pitch.
5. Learn About Funding Options
Discover the latest funding strategies adopted by startups, including seed combinators, angel investing, coworking, local investors, and more. The company of experts in the industry will prove a valuable source of ideas to finance your product.
6. Music-Related Technology
We’re looking for the newest and best ideas. That’s why we’ve dedicated an entire day of the SXSW Accelerator to focus specifically on Music-Related Technologies at the forefront of the industry.
7. Take Advantage of Media Exposure
SXSW attracts a lot of media attention, and SXSW Accelerator is particularly interesting to press outlets looking to break the next exciting technology story. Accelerator presenters can leverage that attention to place their company in the spotlight with ample press opportunities.
8. Register at the Lowest Rate
Entering your product or service in SXSW Accelerator guarantees you the lowest early registration rate of the year.
9. Experience All That SXSW Has to Offer
SXSW Music offers a wealth of exciting opportunities and events, including panel programming, showcases, and, of course, the inspirational experience that only SXSW can deliver. Be a part of it all and enter your innovative product or service to SXSW Accelerator today.
10. Welcome to Austin, Texas
Austin, Texas has long been a hub for freethinking technology movers and shakers. The Central Texas Hill Country has earned the nickname “Silicon Hills” because of the technology industry giants with major operations here and the scores of trailblazing startups and indie tech companies that call Central Texas home. The ever-changing nature of technology and the inclusiveness of its reach make Austin an ideal place to reach out to the larger social web. Did I mention the BBQ?
LastFM-ArtistTags2007
A few years back I created a data set of social tags from Last.fm. RJ at Last.fm graciously gave permission for me to distribute the dataset for research use. I hosted the dataset on the media server at Sun Labs. However, with the Oracle acquisition, the media server is no longer serving up the data, so I thought I would post the data elsewhere.
The dataset is now available for download here: Lastfm-ArtistTags2007
Here are the details as told in the README file:
The LastFM-ArtistTags2007 Data set
Version 1.0
June 2008
What is this?
This is a set of artist tag data collected from Last.fm using
the Audioscrobbler webservice during the spring of 2007.
The data consists of the raw tag counts for the 100 most
frequently occuring tags that Last.fm listeners have applied
to over 20,000 artists.
An undocumented (and deprecated) option of the audioscrobbler
web service was used to bypass the Last.fm normalization of tag
counts. This data set provides raw tag counts.
Data Format:
The data is formatted one entry per line as follows:
musicbrainz-artist-id<sep>artist-name<sep>tag-name<sep>raw-tag-count
Example:
11eabe0c-2638-4808-92f9-1dbd9c453429<sep>Deerhoof<sep>american<sep>14
11eabe0c-2638-4808-92f9-1dbd9c453429<sep>Deerhoof<sep>animals<sep>5
11eabe0c-2638-4808-92f9-1dbd9c453429<sep>Deerhoof<sep>art punk<sep>21
11eabe0c-2638-4808-92f9-1dbd9c453429<sep>Deerhoof<sep>art rock<sep>18
11eabe0c-2638-4808-92f9-1dbd9c453429<sep>Deerhoof<sep>atmospheric<sep>4
11eabe0c-2638-4808-92f9-1dbd9c453429<sep>Deerhoof<sep>avantgarde<sep>3
Data Statistics:
Total Lines: 952810
Unique Artists: 20907
Unique Tags: 100784
Total Tags: 7178442
Filtering:
Some minor filtering has been applied to the tag data. Last.fm will
report tag with counts of zero or less on occasion. These tags have
been removed.
Artists with no tags have not been included in this data set.
Of the nearly quarter million artists that were inspected, 20,907
artists had 1 or more tags.
Files:
ArtistTags.dat - the tag data
README.txt - this file
artists.txt - artists ordered by tag count
tags.txt - tags ordered by tag count
License:
The data in LastFM-ArtistTags2007 is distributed with permission of
Last.fm. The data is made available for non-commercial use only under
the Creative Commons Attribution-NonCommercial-ShareAlike UK License.
Those interested in using the data or web services in a commercial
context should contact partners at last dot fm. For more information
see http://www.audioscrobbler.net/data/
Acknowledgements:
Thanks to Last.fm for providing the access to this tag data via their
web services
Contact:
This data was collected, filtered and by Paul Lamere of The Echo Nest. Send
questions or comments to Paul.Lamere@gmail.com
What’s the TTKP?
Posted by Paul in data, fun, Music, web services on November 9, 2010
Whenever Jennie and I are in the car together, we will listen to the local Top-40 radio station (KISS 108). One top-40 artist that i can recognize reliably is Katy Perry. It seems like we can’t drive very far before we are listening to Teenage Dreams, Firework or California Gurls. That got me wondering what the average Time To Katy Perry (TTKP) was on the station and how it compared to other radio stations. So I fired up my Python interpreter, wrote some code to pull the data from the fabulous YES api and answer this very important question. With the YES API I can get the timestamped song plays for a station for the last 7 days. I gathered this data from WXKS (Kiss 108), did some calculations to come up with this data:
- Total songs played per week: 1,336
- Total unique songs: 184
- Total unique artists: 107
- Average songs per hour: 7
- Number of Katy Perry plays: 76
- Median Time between Katy Perry songs: 1hour 18 minutes
That means the average Time to Katy Perry is about 39 minutes.
Katy Perry is only the fourth most played artist on KISS 108. Here are the stats for the top 10:
| Artist | Plays | Median time between plays |
Average time to next play |
|---|---|---|---|
| Taio Cruz | 84 | 1:07 | 0:34 |
| Rihanna | 80 | 1:27 | 0:44 |
| Usher | 79 | 1:20 | 0:40 |
| Katy Perry | 76 | 1:18 | 0:39 |
| Bruno Mars | 73 | 1:30 | 0:45 |
| Nelly | 56 | 1:44 | 0:52 |
| Mike Posner | 56 | 1:57 | 0:59 |
| Pink | 47 | 2:20 | 1:10 |
| Lady Gaga | 47 | 1:59 | 1:00 |
| Taylor Swift | 41 | 2:17 | 1:09 |
I took a look at some of the other top-40 stations around the country to see which has the lowest TTKP:
| Station | Songs Per Hour | TTKP |
|---|---|---|
| KIIS – LA’s #1 hit music station | 8 | 39 mins |
| WHTZ- New York’s #1 hit music station | 9 | 48 mins |
| WXKS- Boston’s #1 hit music station | 7 | 39 mins |
| WSTR- Atlanta – Always #1 for Today’s Hit Music | 8 | 38 mins |
| KAMP- 97.1 Amp Radio – Los Angeles | 11 | 38 mins |
| KCHZ- 95.7 – The Beat of Kansas City | 11 | 32 mins |
| WFLZ- 93.3 – Tampa Bay’s Hit Music channe | 9 | 39 mins |
| KREV- 92.7 – The Revolution – San Francisco | 11 | 36 mins |
So, no matter where you are, if you have a radio, you can tune into the local top-40 radio station, and you’ll need to wait, on average, only about 40 minutes until a Katy Perry song comes on. Good to know.
NH#1 Mines Follies
10 years ago I read this post in slashdot about a new activity called geocaching – it seemed simple enough: take some item and hide it somewhere in the world, record the latitude and longitude using your GPS receiver, post the location to the Web so that others can find your stash. I had a GPS so I figured I’d give it a try. Unfortunately, there were not any geocaches nearby, so one saturday afternoon I took the GPS, and the 4 kids, went to the local park and hid a cache. What I didn’t realize at the time was that I was placing the first Geocache in New Hampshire (and only the 158th placed in the world). 10 years later there are 1.2 million geocaches scattered around the world, and Geocaching is now a thriving activity enjoyed by thousands of people worldwide. I maintained the cache for a few years, but drifted away from geocaching – but the cache lived on, being maintained by many good samaritan geocachers over the years.
A few weeks ago, I received an email from Michael Noetzel, a local Geocacher who’s taken over maintenance of the cache, inviting me to the 10th anniversary of the cache. I showed up late Friday afternoon expecting to see a half-dozen hardcore geocachers – I was quite surprised to see over 50 people, young and old, had come to celebrate the 10th anniversary of the cache. Here are a couple of pics from the event:
The anniversary celebration at the cache
The plaque they gave me
Lots of people in the woods at the cache
on the way to the cache with an old friend
It was a real fun event – everyone made me feel very special – giving me a plaque, a special rose compass coin and a tee-shirt. Thanks to Nashuan and Bright Shining Stars for making this all happen.
Jennie’s ultimate road trip
Posted by Paul in code, fun, Music, The Echo Nest on October 20, 2010
Last weekend at Music Hack Day Boston, I teamed up with Jennie, my 15-year-old daughter, to build her idea for a music hack which we’ve called Jennie’s Ultimate Road Trip. The hack helps you plan a road trip so that you’ll maximize the number of great concerts you can attend along the way. You give the app your starting and ending city, your starting and ending dates, and the names of some of your favorite artists and Jennie’s Ultimate Road Trip will search through the many events to find the ones that fit your route schedule that you’d like to see and gives you an itinerary and map.
We used the wonderful SongKick API to grab events for all the nearby cities. I was quite surprised at the how many events SongKick would find. For just a single week, in the geographic area between Boston and New York City, SongKick found 1,161 events with 2,168 different artists. More events and more artists makes it easier to find a route that will give a satisfying set of concerts – but it can also make finding a route a bit more computationally challenging too (more on that later). Once we had the set of possible artists that we could visit, we needed to narrow down the list of artists to the ones would be of most interest to the user. To do this we used the new Personal Catalogs feature of the Echo Nest API. We created a personal catalog containing all of the potential artists (so for our trip to NYC from Boston, we’d create a catalog of 2,168 artists). We then used the Echo Nest artist similarity APIs to get recommendations for artists within this catalog. This yielded us a set of 200 artists that best match the user’s taste that would be playing in the area.
The next bit was the tricky bit – first, we subsetted the events to just include events for the recommended set of artists. Then we had to build the optimal route through the events, considering the date and time of the event, the preference the user has for the artist, whether or not we’ve already been to an event for this artist on the trip, how far out of our way the venue is from our ultimate destination and how far the event is from our previous destination. For anyone who saw me looking grouchy on Sunday morning during the hack day it was because it was hard trying to figure out a good cost function that would weigh all of these factors: artist preference, travel time and distance between shows, event history. The computer science folks who read this blog will recognize that this route finding is similar to the ‘travelling salesman problem‘ – but with a twist, instead of finding a route between cities, which don’t tend to move around too much, we have to find a path through a set of artist concerts where every night, the artists are in different places. I call this the ‘travelling rock star’ problem. Ultimately I was pretty happy with how the routing algorithm, it can find a decent route through a thousand events in less than 30 seconds.
Jennie joined me for a few hours at the Music Hack Day – she coded up the HTML for the webform and made the top banner – (it was pretty weird to look over on her computer and see her typing in raw HTML tags with attached CSS attributes – kids these days). We got the demo done in time – and with the power of caching it will generate routes and plot them on a map using the Google API. Unfortunately, if your route doesn’t happen to be in the cache, it can take quite a bit of time to get a route out of the app – gathering events from SongKick, getting the recommendations from the Echo Nest, and finding the optimal route all add up to an app that can take 5 minutes before you get your answer. When I get a bit of time, I’ll take another pass to speed things up. When it is fast enough, I’ll put it online.
It was a fun demo to write. I especially enjoyed working on it with my daughter. And we won the SongKick prize, which was pretty fantastic.
Jennie with the SongKick prize
Great Caesars’ Ghost!
Posted by Paul in Music, The Echo Nest on October 18, 2010
The Echo Nest now has an official Editor in Chief. Eliot Van Buskirk has joined the Echo Nest staff. He’s writing about music apps at Evolver.fm. He already has a whole bunch of great writeups about Music Hack Day Boston and all of the projects that have come out of it. Check it out: evolver.fm
The Echo Nest gets Personal
Posted by Paul in code, Music, playlist, recommendation, remix, The Echo Nest, web services on October 15, 2010
Duke University Archives
Here at the Echo Nest just added a new feature to our APIs called Personal Catalogs. This feature lets you make all of the Echo Nest features work in your own world of music. With Personal Catalogs (PCs) you can define application or user specific catalogs (in terms of artists or songs) and then use these catalogs to drive the behavior of other Echo Nest APIs. PCs open the door to all sorts of custom apps built on the Echo Nest platform. Here are some examples:
Create better genius-style playlists – With PCs I can create a catalog that contains all of the songs in my iTunes collection. I can then use this catalog with the Echo Nest Playlist API to generate interesting playlists based upon my own personal collection. I can create a playlist of my favorite, most danceable songs for a party, or I can create a playlist of slow, low energy, jazz songs for late night reading music.
Create hyper-targeted recommendations – With PCs I can make a catalog of artists and then use the artist/similar APIs to generate recommendations within this catalog. For instance, I could create an artist catalog of all the bands that are playing this weekend in Boston and then create Music Hack Day recommender that tells each visitor to Boston what bands they should see in Boston based upon their musical tastes.
Get info on lots of stuff – people often ask questions about their whole music collection. Like, ‘what are all the songs that I have that are at 113 BPM?‘, or ‘what are the softest songs?’ Previously, to answer these sorts of questions, you’d have to query our APIs one song at a time – a rather tedious and potentially lengthy operation (if you had, say, 10K tracks). With PCs, you can make a single catalog for all of your tracks and then make bulk queries against this catalog. Once you’ve created the catalog, it is very quick to read back all the tempos in your collection.
Represent your music taste – since a Personal Catalog can contain info such as playcounts, skips, and ratings for all of the artists and songs in your collection, it can serve as an excellent proxy to your music taste. Current and soon to be released APIs will use personal catalogs as a representation of your taste to give you personalized results. Playlisting, artist similarity, music recommendations all personalized based on you listening history.
These examples just scratch the surface. We hope to see lots of novel applications of Personal Catalogs. Check out the APIs, and start writing some code.
The Music Hack Day Boston t-shirt
The design by Jocelyn Petko, modeled by Ben Lacker.
Music Machinery 