Updated MIR PhD Theses List

I've updated the list of MIR PhD theses to include the recent work by Antti Eronen on Signal Processing Methods for Audio Classification and Music Content Analysis. Antti covers a broad range of fascinating audio content processing topics such as: instrument classification, classification of ambient environments/backgrounds (libraries, cars, ...), chorus detection, and meter analysis.

Seems like I'm the list is still far from complete. As the following two theses indicate. If you know of any more that I'm missing please let me know. (Thank you Arijit Biswas for your help!)

One that I missed is the work of Michael J. Bruderer on Perception and Modeling of Segment Boundaries in Popular Music. Which describes an interesting series of experiments in which Michael explores which cues listeners use when segmenting music and how they can be modeled.

Another older one I've added is the work of Olivier Gillet Transcription des signaux percussifs. Application à l'analyse de scènes musicales audiovisuelles. Olivier joined Google after his PhD where he worked on the optimization of Google's ad product and on technologies now being used by Google China Music. Olivier is now joining us at Last.fm's to work on fun next generation MIR technologies.

I would also like to mention the Master thesis Implementing a scalable music recommender by Erik Bernhardsson. I really like how Spotify has given him access to their data and let him publish the results. Seems like Spotify was also very happy with his work as they have hired him.

Bang & Olufsen and OFAI

This is probably very old news to some, but I'm a bit behind in blogging.

Yet another really cool product my former colleagues at OFAI have been working on over the last years: integration of content-based playlist generation technologies into the most awesome music hardware out there.

Read more about it here (English) and here (German).

If you can't read German, the perhaps most interest bits: retail price per unit €4.765, 500 pre-orders before the device was available, OFAI and B&O will continue the collaboration, size of the features representing each song: 3.2KB.

FM4 Soundpark and OFAI

My former colleagues at OFAI have been experimenting with audio content based music recommendation for FM4 Soundpark for a while now. (I blogged about it here.) Now they (and in particular Martin Gasser) have taken it a few steps further and implemented a 3D exploration interface using the islands of music metaphor.

It's all in Java and requires special privileges because it needs access to low level graphics card functions. But if you get passed those hurdles here's what you'd see:



(Navigation: space bar, A,W,S,D and mouse)

There is more information about this and other recommendation tools they have developed for Soundpark here (in German).

Last.fm Artist Connections

Playing with Last.fm similar artist data, trying to connect one artist to another through similar artists:



The Beatles -> John Lennon -> Sean Lennon -> Joseph Arthur -> Howie Day -> Teddy Geiger -> Jonas Brothers



ABBA -> Cher -> Madonna -> Róisín Murphy -> Björk -> Radiohead



Metallica -> Iron Maiden -> Paul Di'Anno -> Numbers From The Beast -> Scott Lavender -> Ark Sano -> Frédéric Chopin -> Wolfgang Amadeus Mozart



Brian Eno -> Roxy Music -> Bryan Ferry -> Eurythmics -> Annie Lennox -> Madonna -> Britney Spears

MIR PhD Thesis: Luís Gustavo Martins

Luís Gustavo Martins recently completed his PhD thesis titled A computational Framework for Sound Segregation in Music Signals.

From the abstract: "[...] This dissertation proposes a flexible and extensible Computational Auditory Scene Analysis framework for modeling perceptual grouping in music listening. The goal of the proposed framework is to partition a monaural acoustical mixture into a perceptually motivated topological description of the sound scene (similar to the way a naive listener would perceive it) instead of attempting to accurately separate the mixture into its original and physical sources. [...]"

Luis is probably best known in the MIR community for his contributions to Marsyas (the awesome open source software framework for audio processing with specific emphasis on MIR applications).

If you know of any other dissertations missing in the list of MIR PhDs please let me know.

Visual Listening Charts (Part 2)

Here's a follow-up to my previous attempt to visualize my listening history differently.

Basically, I've been looking for a fun project that would give me plenty of reasons to play with matplotlib.

My preliminary conclusion is that matplotlib is awesome. They couldn't have made it much easier to use for someone already familiar with Matlab.

Recent MIR PhDs

I'm slowly catching up. The following dissertations were added to the list of MIR PhDs:

"Real Time Automatic Harmonisation" by Giordano Cabra. I couldn't find a link to the thesis, but I found a video of the defense. I'd love to see more defense videos (preferably in English).

"Modeling musical anticipation: From the time of music to the music of time" by Arshia Cont.

"Music Recommendation and Discovery in the Long Tail" by Oscar Celma. I highly recommend it!

"From Sparse Models to Timbre Learning: New Methods for Musical Source Separation" by Juan Jose Burred.

UPDATE: I totally missed Yves' announcement on the Music-IR list on Friday. I've added him now too:

"A Distributed Music Information System" by Yves Raimond.

UPDATE 2: Almost forgot that Kris finished recently too:

"Novel Techniques for Audio Music Classification and Search" by Kris West.

Please send me any I might have missed - thanks!