Publication update

This blog has been basically been inactive since last October since being a PostDoc means that there are a whole bunch other things that I am busy with.  And of course, it was winter - that means statistically, there is always someone in the family who is sick (kids bring home every germ that is going around...).

View of Kiel. Source: Johannes Barre 2006, on Wikipedia

But it is spring now!  And I have just returned from DAGA 2017 in Kiel (where we found a very nice Thai restaurant) so time to update some of my work!

First off, my colleagues in Hannover published "Customized high performance low power processor for binaural speaker localization" at ICECS 2016 in Monte Carlo, Monaco (paper on IEEE Xplore), there was the Winter plenary of Hearing4all, and at DAGA 2017, I presented "Pitch features for low-complexity online speaker tracking", and Sarina (Ph.D. student I'm co-supervising) presented "A distance measure to combine monaural and binaural auditory cues for sound source segregation", both of which can be found on my homepage.  In the pipeline is now "Real-time Implementation of a GMM-based Binaural Localization Algorithm on a VLIW-SIMD Processor" by Christopher, which has been accepted and will be presented at ICME 2017 in Hong Kong in July, and I submitted a paper ("Segregation and Linking of Speech Glimpses in Multisource Scenarios on a Hearing Aid") to EUSIPCO 2017; that one is still in review.

I was also teaching a class in the past semester ("5.04.4223 Introduction into Music Information Retrieval") which, because it's a brand new class took a crazy amount of work to prepare for - but I think the students really enjoyed it, and I saw some very good code being written for the final project.

Now back to real work (writing more papers, that is)!  (Well, there's one or two topics I'll put on the blog in the next little while, too.  Later.)

A (very) short trip to Korea

Panorama view from my room at the Nest Hotel in Incheon.  The Incheon Airport is visible on the right.

Earlier this month, I was in Incheon, South Korea, to present a talk at the Symposium for "Statistical physics, machine learning, and its application to speech and pattern recognition", organized by Prof. Kang-Hun Ahn as part of the Korea Institute for Advanced Study (KIAS).  I was specifically invited to give a talk there (along with Jörg Lücke and Steven van de Par). One does not refuse such an invitation, esp. as a post-doc trying to make an academic career happen.

As a conference, the event was very good, in both of scientific content and forging connections that hopefully can  continue in the future.  Many interesting discussions happened outside the sessions, too.

The location of the Symposium banquet. It was excellent.  Don't ask me for the name though; but I can give the coordinates: 37°25'53.1"N 126°25'27.0"E

The trip was bizarre for me for one reason, though.  It's the first time I traveled that far just to present at a conference.  Unfortunately, this symposium was scheduled not long after I had returned from Italy (where I was at MLSP 2016, coupled with a 1 week vacation), and the week before classes start here at the University of Oldenburg; so I had no time to do any sightseeing in Korea.  I literally arrived the day before the first day of the symposium, and left the morning after the last day.  Total time in Korea: about 66 hours. Total time flying there and back: 30 hours. We (myself, Jörg, and Steven) never went further than about 5 km from the Airport.

I certainly hope to go to Korea again, but then stay a little longer! There is so much to see, and I have friends in Japan I'd like to visit, too.  (I've been to Jeju before, so I know Korea can be very beautiful. Next time I'd like to bring the wife and kids along!)

MLSP2016 paper: Speaker Tracking for Hearing Aids

MLSP 2016 poster, the print version
can be found here.

Yesterday, I presented my poster at the 2016 IEEE International Workshop on Machine Learning for Signal processing. I think it was received pretty well, there were several people that talked to me, and we had very good discussions. The biggest problem (and typical for all poster sessions) was that there were other good posters being presented, and I couldn't really spend time talking to the other authors at that session. However, over the next few days I'll have a chance to chat with them, so it's all good.

The beach of the conference venue,
with view towards Salerno.

My own paper I'm presenting is entitled "Speaker Tracking for Hearing Aids", and it basically a method to link speech utterances spoken at different times by the same speaker, a classic problem also found in speaker diarization (but I don't need to do segmentation).  My method however is optimized for low computational complexity (for hearing aids), yet reaches comparable performance to typical far more complex methods.  You can find the abstract, paper, and poster (seen in the pic) on my homepage.

Overall, I like these small, highly focused conferences - and being in a nice sunny environment is not to be sneezed at either.

A simple scikit-learn classifier based on Gaussian Mixture Models (GMM)

When I started switching to Python for my work on CASA, it wasn't entirely clear to me how to use the sklearn GMM (sklearn.mixture.GMM) for classification.  Turned out a bit easier than expected (yay for scikit-learn!), but for others, here is my implementation of a class that behaves like the other classifiers (eg. sklean.svm.SVC).  All you need to decide is how many Gaussians you want to model your data with, and off you go.

Link to Github repo. A Jupyter notebook shows a sample use.

Why isn't something like this in sklearn yet?  Well, turns out someone did propose it already (no surprise) in a much more general way: see this discussion on GitHub.  (I myself was pointed there when I asked about my own code)  My bit of code is far more primitive, but I hope easier to understand.