Luke Barrington lukeinusa@gmail.com

I'm pleased to announce that I have completed my Ph.D! The final step was getting my Herd It paper published in PNAS.
I now work at , a company that I founded along with 3 other genii.
Tomnod applies crowdsourcing and machine learning to massive geo-spatial challenges.
We engage thousands of people online to help find the tomb of Genghis Khan, map earthquake damage in Christchurch or identify the best St. Patrick's Day parties!
I'll keep this site alive for the time being but, to stay up to date with my current work, check out the Tomnod blog and join the crowd!



I'm a Ph.D student in Electrical and Computer Engineering from the University of California, San Diego

I am a founder of the UCSD Computer Audition Lab where I research: I am affiliated with the CoSMaL group and Prof. Gary Cottrell.
I am searching for the tomb of Genghis Khan with the Valley of the Khans project.

I play guitar and sing with Telefunk.

Please get in touch: lukeinusa@gmail.com

DEFENDED!!!!!! Dec 2011
I am very proud to report that I successfully defended my Ph.D thesis on December 2nd, 2011! The title of my dissertation is "Machines that Understand Music". My committee of Profs Gary Cottrell, Lawrence Saul, Bhaskar Rao and Nuno Vasconcelos gave me great guidance over the years and were very pleased with my defense. I'm also very grateful to the many friends who attended the talk and helped me celebrate afterwards! Of course, none of this would have been possible without the support of my advisor, Prof. Gert Lanckriet.
Onto the next adventure!

DTM Code released June 2011
I am pleased to release a Python implementation of the Dynamic Textures Mixture model that I used for music segmentation in my recent IEEE journal paper. The DTM code takes a series of audio feature vectors, merges them into longer "frames" and models each frame as a Dynamic Texture. Frames with the same Texture are assigned to the same audio segment (e.g., chours, verse, ...).
Download the code here
If you use this code in your research or if you have any questions or suggestions, please drop me a line -- I'd love to hear about it!

Journey to the Valley of the Khans August 2010
I've just returned from a month-long adventure in Mongolia, working with Dr. Albert Yu-Min Lin's Valley of the Khans project and National Geographic to search for the tomb of Genghis Khan!
We designed an built a human computation application to examine satellite images of the Mongolian steppe where Genghis lived 800 years ago. So far, over 6,000 "virtual explorers" have tagged more than a million sites of archaeological interest.
My job in Mongolia was to wake up every morning in our ger, download the new tags, identify the most interesting sites and then jump on my horse and check them out. Check out the expedition blog where I write about our discoveries.
Science in action!

New Scientist June 2010

"Never easy to categorise"
New Scientist featured a story about how MIR researchers like Dan Ellis, Luciano da F. Costa and I are making progress towards computerised music critics that can help everyone find great tunes.
The article mentions the "Bohemian Rhapsody problem" that I describe in my recent TASLP paper along with this great pic of Freddie ... perfect!

Qualcomm Innovation Fellowship May 2010
I'm proud, honored and very happy to have been awarded a Qualcomm Innovation Fellowship.
My partner in crime, Brian, and I pitched our vision of "Location-, Demographic-, Preference- and Content-based Music Discovery".
Now, with Qualcomm's help, we're actually going to make this music fan's dream a reality!

3/3 - ISMIR 2010 May 2010
Congratulations to Brian McFee, Riccardo Miotto and Emanuele Coviello, three of CAL's finest who all had first-author papers accepted to ISMIR 2010!
I'm doubly happy because I was second author on all of them - check out my publications section. Utrecht, here we come!

The Science Network April 2010
A video of my talk on "Human Powered Machine Learning" has been posted on the Science Network.
I really enjoyed presenting my work on Computer Audition and Herd It to the audience at the Temporal Dynamics of Learning Center.
Finally I have confirmation of the fact that I talk too fast!

CALab undergrads win UCSD Yahoo! Hack Day April 2010
I'm very proud of Andrew Huynh and David Vanoni, two undergrads who have been working with me at CALab for the past year. Their "Rock My World" app won first prize at the Yahoo Hack Day. I had an idea for an app that would find great gigs playing in your neighborhood and, in 24hrs, they made it a reality!
Download Rock My World to your iPhone (open it in Safari and then choose "+ add to homepage").

Slashdotted! Nov 2009
A story about my work on building a music recommender that could be smarter than Genius by Jacobs School reporter Daniel Kane attained nerdvana by getting posted on Slashdot! This led to over 2,000 new players checking out Herd It (and a few server crashes). w00t!

Smarter Than Genius? Oct 2009
I just gave a talk at ISMIR in Kobe, Japan about my paper "Smarter Than Genius?", an analysis of iTunes' music recommender system. The talk was great, I had some really interesting questions and comments and it's always fun to be at ISMIR. Read the press release or download my slides

Modeling Music as a Dynamic Texture Oct 2009
My paper has just been accepted to IEEE Transactions on Audio, Speech and Language Processing! This paper presents a new statistical model of music, adapted from Prof. Antoni Chan's work on video, that really takes time into account. Also, it shows how to solve the Bohemian Rhapsody problem!

Listen to the 35-second version of Bohemian Rhapsody!

Herd It offical launch! Oct 2009
Afer years (and years) of development, testing, design, refinement, bug fixing, testing, tweaking, and playing, Herd It is fully ready to rock!
I've added a blog and a Twitter feed (@herdit) as well as a bunch of new gameplay features. Now we are making a BIG effort to promote the game - so tell your friends, newspaper, blog readers... tell everyone to play Herd It!
Once lots of people to play Herd It and we collect some great data then I can graduate!

Herd It in the news April 2009
Phenomenal reception to the Beta release of my music annotation game Herd It!
First we got written up in Voice of San Diego and that led to a news spot on Channel 6 (unfortunately, I was in Taiwan at ICASSP so Gert had to present!)
Then Robyn Williams interviewed Gert and I on the Science Show, resulting in loads of new users (at some times, too many for our server!).
Play Herd It.

ICASSP and the Bohemian Rhapsody Problem April 2009
Just gave a talk at ICASSP in Taipei, Taiwan about automatic music segmentation using dynamic texture mixture models of music.
Check out how we use this method to solve the "Bohemian Rhapsody problem" of automatically tagging muscially diverse songs!
UPDATE May 2009
An article about this research and how it contributes to our music search engine just got posted on the Jacob's School of Engineering Site, UCSD's site and EurekAlert.org!

Harmonograph Mar 2009
I built a virtual harmonograph that is a great way to visualize musical intervals - and quite trippy.
You can read more about it on my blog.

Entertainment Tired Love New Speech! Dec 2008
News of my talk at the Math Club last month has appeared in the Swedish newspaper, DN.
(no, I can't understand it either. Try the humourously flawed Google translation!).
Download my slides on "Machines that Understand Music".

NIMBLE at large Nov 2008
My first journal paper has just been published!

Best in the biz Oct 2008
My entry to the 2008 MIREX auto-tagging contest placed 1st out of eleven! abstract poster

Twitter (@lukeinusa):

A selection of media stories that have featured my research...

Luke Barrington's Publications

Barrington Turnbull & Lanckriet - Game-Powered Machine Learning.
Proceedings of the National Acadmeny of Sciences of the United States of America. (Herd It game)

McFee, Barrington and Lanckriet - Learning content similarity for music recommendation
To appear in IEEE Transactions on Audio, Speech and Language Processing, 2012.

Barrington, Ghosh, Greene, Har-Noy, Berger, Gill, Lin and Huyck - Crowdsourcing earthquake damage assessment using remote sensing imagery
Annals of Geophysics 54(6) 2011

Barrington, Har-Noy, Ricklin, Stastny and Rainey - Computer Vision methods for Ship Identification in Cloudy Satellite Imagery
IEEE Applied Imagery Pattern Recognition (AIPR) Workshop 2011


McFee, Barrington & Lanckriet - Learning Similarity from Collaborative Filters.
ISMIR 2010

Miotto, Barrington & Lanckriet - Improving Auto-tagging by Modeling Semantic Co-occurrences.
ISMIR 2010

Coviello, Barrington, Chan & Lanckriet - Automatic Music Tagging With Time Series Models.
ISMIR 2010

Barrington, Chan & Lanckriet - Modeling Music as a Dynamic Texture.
IEEE Transactions on Audio, Speech and Language Processing, 18(3), 602-612. (bibtex)(project page)(code)


Barrington, Oda & Lanckriet - Smarter Than Genius? Human Evaluation of Music Recommender Systems.
ISMIR 2009 (slides)

Barrington, Turnbull, O'Malley & Lanckriet - User-Centered Design of a Social Game to Tag Music.
HCOMP 2009 (slides)

Barrington, Turnbull, Yazdani & Lanckriet - Combining Audio Content and Social Context for Semantic Music Discovery.
SIGIR 2009

Barrington, Chan & Lanckriet - Dynamic Texture Models of Music.
ICASSP 2009 (slides)


Barrington, Marks, Hsiao & Cottrell - NIMBLE: A Kernel Density Model of Saccade-Based Visual Memory.
Journal of Vision, 8(14):17, 1-14

Barrington, Yazdani, Turnbull & Lanckriet - Combination of Feature Kernels for Semantic Music Retrieval.
ISMIR 2008 (poster)

Turnbull, Barrington & Lanckriet - Five Approaches to Collecting Tags for Music.
ISMIR 2008

Turnbull, Barrington, Torres & Lanckriet 2008 - Semantic Annotation and Retrieval of Music and Sound Effects.
IEEE Transactions on Audio, Speech, and Language Processing, 16(2), 467-476


Torres, Turnbull, Barrington & Lanckriet 2007 - Identifying Words that are Musically Meaningful.
International Symposium on Music Information Retrieval (ISMIR), Vienna, September 2007

Turnbull, Liu, Barrington & Lanckriet 2007 - A Game-Based Approach for Collecting Semantic Annotations of Music.
International Symposium on Music Information Retrieval, Vienna, September 2007

Turnbull, Barrington, Torres & Lanckriet 2007 - Towards Musical Query-by-Semantic-Description using the CAL500 Data Set.
ACM Special Interest Group on Information Retrieval, Amsterdam

Barrington, Marks & Cottrell 2007 - NIMBLE: A Kernel Density Model of Saccade-Based Visual Memory.
Cognitive Science Society Conference, Nashville

Barrington, Chan, Turnbull & Lanckriet 2007 - Audio Information Retrieval Using Semantic Similarity.
International Conference on Acoustics, Speech and Signal Processing, Hawai'i


Turnbull, Barrington, Torres & Lanckriet 2006 - Modeling the Semantics of Sound.
NIPS Workshop on Advances in Models for Acoustic Processing, Vancouver (poster)

Turnbull, Barrington & Lanckriet 2006 - Modelling Music and Words.
International Symposium on Music Information Retrieval, Victoria

Barrington & Cottrell 2006 - Automatic Visual Integration - Defragmenting the Face.
Cognitive Science Society Conference, Vancouver (slides 492kb zip file)

Barrington & Cottrell 2006 - A Fragment-Based Memory Model of Saccadic Vision.
Cognitive Neuroscience Society Meeting, San Francisco (abstract)

Barrington, Lyons, Diegmann & Abe 2006 - Ambient Display Using Musical Effects.
Intelligent User Interfaces, Sydney (Poster)




Click here to watch me and my Tomnod co-founder, Albert Lin, at TEDx Intuit talking about how Tomnod wants to Crowdsource the World.
(hint: the password is the name of my company).




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My talk at UCSD's Temporal Dynamics of Learning Center all-hands meeting on "Human Powered Machine Learning", Jan 23rd 2010 (Slides).




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Overview of how our music discovery engine can help musicians like my friends SO3, Juna and Beat7.




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A video of me describing how Herd It works and how it helps undiscovered artists.


Audio clip of Gert and me on the Science Show talking about Herd It .

My talk at ISMIR 2009 about our experiments on iTunes Genius and comparisons to automatic recommender systems (slides) (paper)

My Math Club lecture "Machines That Understand Music", Nov 16th 2008 (25Mb PDF)

Slides for PEN Online talk on NIMBLE, August 21st 2006 (583kb zip file)

Slides for GURU talk on Greeble Sonification, March 13th 2006 (1.8Mb .tar file)

Slides for Affective Effects AI seminar October 14th, 2005 (800kb .ppt file)

Slides for PEN Online Meeting April 20th, 2005 (2Mb .ppt file)

Python implementation of the Dynamic Textures Mixture model from my 2010 IEEE paper. (2.7Mb tar file)

Audio feature extraction code for CSE253 lecture, Feb 29th 2008 (16kb zip file)

My brain!

San Diego surf report

I built an online Harmonograph, a weird, wonderful way to visualize musical intervals

Download my CV in PDF format