The Echno Nest made it on Techcrunch!
Interestingly Techcrunch seems to think that The Echo Nest is about genre classification (second sentence in their blog post). I doubt they heard that from Brian.
One reader raised an interesting question: "[...] do we really need a computerized pandora?" It's nice to see something like this discussed outside of the music-ir mailing list!
I really like The Echo Nest's very open approach to demonstrate the technologies they got. Besides being of interest to anyone in MIR I'm sure it also makes it a lot easier to attract interest to their APIs and communicate what kind of problems can be solved with them. But I'm not sure if I like the redesign of their webpage, I somehow had gotten used to the simplicity of their original one. I'm very curious what their next demonstrations will be... maybe some web crawling based stuff?
See also Paul's post about this is my jam.
Sunday, 30 March 2008
Friday, 7 March 2008
Thoughts on Autotagging
I've recently spent a lot of time looking at tags. I'm fascinated by how creative listeners are when it comes to inventing new tags for the music they care about. And I'm fascinated by how small communities adapt these newly invented terms as quickly as they tune into a new radio station. This constantly changing and seemingly endless vocabulary of words to describe music makes me wonder if research on automatically classifying or tagging music will ever be able to catch up.
If you think research is catching up, check out the 22,703 shades of metal, or the 11,929 shades of pop, or the 29,940 shades of rock at Last.fm.
See also Paul's experiments on creating a taxonomy of metal and gothic tags.
See also Mike's recent results on autotagging of music (which includes some impressive numbers).
If you think research is catching up, check out the 22,703 shades of metal, or the 11,929 shades of pop, or the 29,940 shades of rock at Last.fm.
See also Paul's experiments on creating a taxonomy of metal and gothic tags.
See also Mike's recent results on autotagging of music (which includes some impressive numbers).
Monday, 11 February 2008
Simple Stuff
Jeff Hammerbacher from Facebook’s team on data and analytics gave an interesting talk and it can be viewed here (which might be broken, here is a direct link). I’d highly recommend it to anyone interested in what happens behind the scenes on websites dealing with a lot of interesting data.
Some of the stuff he talks about is related to what happens at Last.fm. For example, at Last.fm we also use Hadoop.
I found the part around minutes 33-38 most interesting. He talks about the skills needed to work with their data. He mentions that being able to write code is a must. He mentions that most of the people on his team write more code than they did in their previous positions. And he mentions that very simple statistical tools such as curve fitting and understanding statistical significance can be used to solve most of their learning from data challenges. He talks about how visualizing data is very important (e.g. to identify and understand outliers).
Obviously music recommendation is a much more complex problem than any of the challenges Facebook is facing. Scrobbles, tags, skipping behaviour, etc require very different treatment than the data Facebook gathers. Or maybe not?
To some of the most interesting things I’ve had the pleasure to work on at Last.fm I’ve only applied very basic statistical techniques: non-linear curve fitting and measuring the significance of improvements. However, while the “machine learning” parts could hardly be any simpler, the complexity of dealing with terabytes is something completely different.
Btw, at Last.fm we are hiring someone to work on data and analytics and we also got a position related to data warehousing. Both positions would be facing challenges very closely related to the stuff Jeff talks about. Except that the data we have is a lot more interesting! It made me a bit sad to hear that one of the things they were actually looking at is communication streams between universities… you’d think they’d have a lot more interesting insights to gain? ;-)
Some of the stuff he talks about is related to what happens at Last.fm. For example, at Last.fm we also use Hadoop.
I found the part around minutes 33-38 most interesting. He talks about the skills needed to work with their data. He mentions that being able to write code is a must. He mentions that most of the people on his team write more code than they did in their previous positions. And he mentions that very simple statistical tools such as curve fitting and understanding statistical significance can be used to solve most of their learning from data challenges. He talks about how visualizing data is very important (e.g. to identify and understand outliers).
Obviously music recommendation is a much more complex problem than any of the challenges Facebook is facing. Scrobbles, tags, skipping behaviour, etc require very different treatment than the data Facebook gathers. Or maybe not?
To some of the most interesting things I’ve had the pleasure to work on at Last.fm I’ve only applied very basic statistical techniques: non-linear curve fitting and measuring the significance of improvements. However, while the “machine learning” parts could hardly be any simpler, the complexity of dealing with terabytes is something completely different.
Btw, at Last.fm we are hiring someone to work on data and analytics and we also got a position related to data warehousing. Both positions would be facing challenges very closely related to the stuff Jeff talks about. Except that the data we have is a lot more interesting! It made me a bit sad to hear that one of the things they were actually looking at is communication streams between universities… you’d think they’d have a lot more interesting insights to gain? ;-)
Thursday, 7 February 2008
Web Services for Researchers
It just occurred to me how soon every research lab might be offering a long list of web services. Bandwidth is not a limiting factor. Building a web service is not that hard as it was 5 years ago. It's a great way to share without giving away code (and IP). It's also user friendlier as it doesn't require installing someone else's most likely buggy code on your own system. And it's potentially a great way to make money, too!
I wonder if I'm the last one to realize this? :-)
Anyway, what has helped me realize this was Thomas Lidy's announcement of his teams new web service, and The Echo Nest's web services that I recently found out about through Paul. Both allow you to upload music, extract features from the audio signal, and send them back to you.
I just gave both a try and they worked very smoothly. The two pictures below show results for the same track. The first one is created with the processing music visualization tool provided by The Echno Nest, the second one using Matlab to analyze the fluctuation pattern that Tom's tool extracts.
I wonder if the Echo Nest's service would crunch 100k tracks. (I believe there are at least a few research groups already dealing with collections beyond 100k tracks.) The service Tom announced is limited to 100 tracks/day and a maximum of 300 total per voucher (which requires you to sign up with your email address). Anyway it's a great start. And it seems that Tom will soon be making more announcements on further services that allow anyone to visually organize their music collections using a metaphor of geographic maps. Nice!
Btw, the Last.fm web services also seem to be very popular amongst researchers, at least some have been hitting them very hard ;-)
And one of the most eagerly anticipated web services is probably the MIREX DIY web service which was announced at ISMIR 2007 by Stephen Downie's team. The service will allow researchers to upload their implementations and receive evaluation results in return. Which will make it very easy for researchers to test if they are heading in the right direction.
I wonder if I'm the last one to realize this? :-)
Anyway, what has helped me realize this was Thomas Lidy's announcement of his teams new web service, and The Echo Nest's web services that I recently found out about through Paul. Both allow you to upload music, extract features from the audio signal, and send them back to you.
I just gave both a try and they worked very smoothly. The two pictures below show results for the same track. The first one is created with the processing music visualization tool provided by The Echno Nest, the second one using Matlab to analyze the fluctuation pattern that Tom's tool extracts.
I wonder if the Echo Nest's service would crunch 100k tracks. (I believe there are at least a few research groups already dealing with collections beyond 100k tracks.) The service Tom announced is limited to 100 tracks/day and a maximum of 300 total per voucher (which requires you to sign up with your email address). Anyway it's a great start. And it seems that Tom will soon be making more announcements on further services that allow anyone to visually organize their music collections using a metaphor of geographic maps. Nice!
Btw, the Last.fm web services also seem to be very popular amongst researchers, at least some have been hitting them very hard ;-)
And one of the most eagerly anticipated web services is probably the MIREX DIY web service which was announced at ISMIR 2007 by Stephen Downie's team. The service will allow researchers to upload their implementations and receive evaluation results in return. Which will make it very easy for researchers to test if they are heading in the right direction.
Tuesday, 5 February 2008
2 PhDs and 1 MSc
Matthew Davies recently made his PhD (Towards Automatic Rhythmic Accompaniment) available online.
Arturo Camacho recently announced on the music-ir list that his PhD (SWIPE: A Sawtooth Waveform Inspired Pitch Estimator for Speech and Music) and the corresponding Matlab code are available online.
Claudia Wronski recently finished her Master's thesis (in German) on "Die veränderten Zugriffsmöglichkeiten auf die Ressource Musik – Auswirkungen auf das Kauf-, Nutzungs- und Rezeptionsverhalten der Musikkonsumenten" (freely translated: the changing access to music and its impact on shopping and consumption habits of music listeners). She covers topics such as how the music culture is changing, the crisis of the music industry, the long tail, the emancipation of artists, and the future of music.
Claudia is an active Last.fm user, and has successfully been leading a very interesting user group: The Special Interest Tag Radio Collective.
Arturo Camacho recently announced on the music-ir list that his PhD (SWIPE: A Sawtooth Waveform Inspired Pitch Estimator for Speech and Music) and the corresponding Matlab code are available online.
Claudia Wronski recently finished her Master's thesis (in German) on "Die veränderten Zugriffsmöglichkeiten auf die Ressource Musik – Auswirkungen auf das Kauf-, Nutzungs- und Rezeptionsverhalten der Musikkonsumenten" (freely translated: the changing access to music and its impact on shopping and consumption habits of music listeners). She covers topics such as how the music culture is changing, the crisis of the music industry, the long tail, the emancipation of artists, and the future of music.
Claudia is an active Last.fm user, and has successfully been leading a very interesting user group: The Special Interest Tag Radio Collective.
Sunday, 27 January 2008
Fun with Audio Analysis
Paul just blogged about it: The Echo Nest are demonstrating some of the stuff they have been working on. The one I like best is "automatic song" (which they say is a composition from automatically combining about 50 songs).
I'm curious what impact their API to extract features from audio will have on MIR research. Seems like they are also targeting artists who use processing to visualize music content. I'd like to see videos of their music visualizations.
I'm curious what impact their API to extract features from audio will have on MIR research. Seems like they are also targeting artists who use processing to visualize music content. I'd like to see videos of their music visualizations.
Wednesday, 23 January 2008
The future of MIR?
The European Commission (Unit DG INFSO/E2) is planning to invest 2B€ in research and development (2009-2010, FP7). They recently sent out emails asking for comments from researchers:
“[…] we would very much like to hear your views on what you think are the most pressing problems and ripe opportunities in your field. We are interested as much in scientific advances as in innovative applications or infrastructural initiatives in domains where they are likely to have a large positive impact.”
(The context is “knowledge technologies, interactive media and online content”.)
It’s an interesting question to think about.
I’m tempted to point them to work on unstructured collaborative tagging of music, ie, folksonomies. There are lots of interesting opportunities there, some of which might still be there by the time the FP7 projects start.
If you have any ideas, let the EC know:
http://cordis.europa.eu/ist/kct/fp7-consultation.htm
UPDATE: Jeremy points out some interesting topics the EU should funding in the comments.
“[…] we would very much like to hear your views on what you think are the most pressing problems and ripe opportunities in your field. We are interested as much in scientific advances as in innovative applications or infrastructural initiatives in domains where they are likely to have a large positive impact.”
(The context is “knowledge technologies, interactive media and online content”.)
It’s an interesting question to think about.
I’m tempted to point them to work on unstructured collaborative tagging of music, ie, folksonomies. There are lots of interesting opportunities there, some of which might still be there by the time the FP7 projects start.
If you have any ideas, let the EC know:
http://cordis.europa.eu/ist/kct/fp7-consultation.htm
UPDATE: Jeremy points out some interesting topics the EU should funding in the comments.
Subscribe to:
Posts (Atom)