Inspired by Paul's constant flow of ISMIR blog posts I thought I should give it a try and post some thoughts as well.
First of all, the organizers did a wonderful job organizing ISMIR. I already wrote about what I think about the electronic proceedings. I was also very happy to see that they did not waste unnecessary resources and skipped the silly conference bag thing.
I very much enjoyed giving the social tags tutorial with Paul. It worked out really well, and although I knew Paul's slides since weeks, I found it fascinating to listen to Paul talk about them.
So far ISMIR has by far exceeded my expectations. I've had the pleasure to meet many in person that I previously hadn't had the opportunity to meet. I've also had the pleasure to see many very interesting posters. Unfortunately I've also managed to miss many that I wanted to see. I guess there's never enough time to see everything.
Last night's banquet was great too. In particular I enjoyed the conversations with Etienne from Pandora.
The recommendation panel today was fun, too.
Showing posts with label ISMIR. Show all posts
Showing posts with label ISMIR. Show all posts
Tuesday, 16 September 2008
Wednesday, 27 August 2008
ISMIR Proceedings 2008! Wow!
I'm extremely impressed. The ISMIR proceedings are online. Whoever wants a printed copy can organize it themselves (it couldn't be much easier). Some might also want to only print the papers they are interested in. And some might be happy to have only an electronic version.
It's always been a pain to drag the heavy ISMIR proceedings home. And it always felt like a huge waste of paper.
I heard Juan and Youngmoo talk about this idea a year ago in Vienna (at last year's ISMIR). I'm very happy to see that they found a solution that should make everyone happy.
Juan writes in his email:
We hope that you will like this new approach to printing the proceedings which we intend to be more cost effective, more convenient, and, with luck, more environmentally friendly than mass printing of proceedings for all attendees who may not wish to carry a printed copy around.
Wonderful! :-)
It's always been a pain to drag the heavy ISMIR proceedings home. And it always felt like a huge waste of paper.
I heard Juan and Youngmoo talk about this idea a year ago in Vienna (at last year's ISMIR). I'm very happy to see that they found a solution that should make everyone happy.
Juan writes in his email:
We hope that you will like this new approach to printing the proceedings which we intend to be more cost effective, more convenient, and, with luck, more environmentally friendly than mass printing of proceedings for all attendees who may not wish to carry a printed copy around.
Wonderful! :-)
Wednesday, 25 June 2008
ISMIR'08 Student Travel Award
It's wonderful to see Sun Microsystems sponsoring student travel awards for this year's ISMIR. Submission deadline for applications is July 4th - very soon!
I highly recommend applying for an award even if it might seem like a bureaucratic burden. Sure, any student who gets an award will still need to find additional sources of funding. However, it's always easier to find smaller amounts of money, and as a researcher it is not unusual to spend a lot of time writing project proposals asking for grants. Student travel awards are a great way to start practicing! And writing one page yourself and asking your professor to write a recommendation is actually not a lot of effort. Btw, professors deal with recommendations very frequently, they shouldn't complain if you ask them to write you one :-)
I remember when I received a student travel award for the ACM KDD 2003: It was lots of fun because students who won the award also got a chance to participate in the organization. And helping in the organization of such a huge conference was a great experience.
I highly recommend applying for an award even if it might seem like a bureaucratic burden. Sure, any student who gets an award will still need to find additional sources of funding. However, it's always easier to find smaller amounts of money, and as a researcher it is not unusual to spend a lot of time writing project proposals asking for grants. Student travel awards are a great way to start practicing! And writing one page yourself and asking your professor to write a recommendation is actually not a lot of effort. Btw, professors deal with recommendations very frequently, they shouldn't complain if you ask them to write you one :-)
I remember when I received a student travel award for the ACM KDD 2003: It was lots of fun because students who won the award also got a chance to participate in the organization. And helping in the organization of such a huge conference was a great experience.
Thursday, 22 May 2008
ISMIR'08 Reviewing
ISMIR 2008 seems extremely well organized. I've been only watching from the side line this year (for the first time since 2002 I haven't submitted a paper myself) but the bits and pieces I've seen seem great.
I like how reviews are double blind this year.
I like how authors get a chance to respond to reviews. And reviewers get a chance to reconsider their ratings after seeing the response of the authors, and what their fellow reviewers wrote.
However, and this strikes me as fascinating: I get to see the name of my fellow reviewers! (To be more accurate: I only get the see reviews and names of reviewers who reviewed the same content I did.) First I thought it was a bug in the system (I even felt the urge to instantly report it to the program chairs). But it seems like the whole system is designed around exposing the real names of the reviewers to the fellow reviewers: I was just sent an email with the email addresses of all my fellow reviewers.
I think I've never experiences such openness in any of the review processes I've been involved in. It's fascinating, but it makes me wonder if that might lead to reviewers being more reluctant to write critical remarks in the future? Especially in such a small community as the ISMIR community, one of the fellow reviewers might be a colleague of one of the authors etc. While I think it's a good idea to publish reviews and a response to those (I did so for one of my publications last year here), I don't think it's necessarily a good idea to expose the reviewers without their consent.
I like how reviews are double blind this year.
I like how authors get a chance to respond to reviews. And reviewers get a chance to reconsider their ratings after seeing the response of the authors, and what their fellow reviewers wrote.
However, and this strikes me as fascinating: I get to see the name of my fellow reviewers! (To be more accurate: I only get the see reviews and names of reviewers who reviewed the same content I did.) First I thought it was a bug in the system (I even felt the urge to instantly report it to the program chairs). But it seems like the whole system is designed around exposing the real names of the reviewers to the fellow reviewers: I was just sent an email with the email addresses of all my fellow reviewers.
I think I've never experiences such openness in any of the review processes I've been involved in. It's fascinating, but it makes me wonder if that might lead to reviewers being more reluctant to write critical remarks in the future? Especially in such a small community as the ISMIR community, one of the fellow reviewers might be a colleague of one of the authors etc. While I think it's a good idea to publish reviews and a response to those (I did so for one of my publications last year here), I don't think it's necessarily a good idea to expose the reviewers without their consent.
Monday, 1 October 2007
Life after ISMIR 2007
As usual after an ISMIR I’m totally burnt out. The program was intense. My brain is still trying to absorb all the interesting conversations, ideas, results, and theories that are echoing in my ears. Some of the things I saw made me realize how close we are to reach some of the scenarios we’ve been talking about in the last 5 years (for example, Klaas Bosteels demonstrated a content-based playlist generator that learns from user feedback which he implemented on his tiny MP3 player). Other things made me reconsider assumptions I’ve made in the past (for example Hamish Allan et al. presented interesting work on music similarity: "Methodological Considerations in Studies of Musical Similarity").
It was also wonderful to have the opportunity to spend time with people that seem very familiar although I only see them once every one or two years. It’s strange how reading papers can make the authors seem so familiar.
One of the many highlights of ISMIR 2007 was when Don Byrd announced the locations of future ISMIRs. I was particularly happy to hear that ISMIR 2009 will be organized by Masataka Goto et al. (in Japan!). However, ISMIR 2008 organized by Youngmoo Kim, Dan Ellis, and Juan Bello et al. (US) and ISMIR 2010 organized by Frans Wiering et al. (Netherlands) will surely be great, too. It’s good to see ISMIR, for the first time in its history (afaik), planed out for 3 years in advance. And I heard some rumors that ISMIR 2011 will be held in Vienna again because it was such a huge success ;-)
It was also wonderful to have the opportunity to spend time with people that seem very familiar although I only see them once every one or two years. It’s strange how reading papers can make the authors seem so familiar.
One of the many highlights of ISMIR 2007 was when Don Byrd announced the locations of future ISMIRs. I was particularly happy to hear that ISMIR 2009 will be organized by Masataka Goto et al. (in Japan!). However, ISMIR 2008 organized by Youngmoo Kim, Dan Ellis, and Juan Bello et al. (US) and ISMIR 2010 organized by Frans Wiering et al. (Netherlands) will surely be great, too. It’s good to see ISMIR, for the first time in its history (afaik), planed out for 3 years in advance. And I heard some rumors that ISMIR 2011 will be held in Vienna again because it was such a huge success ;-)
Sunday, 23 September 2007
ISMIR Highlight: Recommendation Tutorial
Paul Lamere and Oscar Celma did a wonderful job presenting the recommendation tutorial. I wouldn't be surprised if this turns out to be my personal highlight of ISMIR 2007. They presented an overview of all the standard techniques used for recommendations, they talked about the typical (and unsolved) problems recommenders face, they had plenty of examples, and they also presented results from an evaluation of recommenders. The parts I personally liked best were the in depth analysis of tags and folksonomies, the part they called "novelty and relevance" (with interesting ideas on how to reach deeper into the long-tail), the analysis of artist similarity networks, and the evaluation of recommenders. They also made an interesting point about how nice it would be to have something like a Netflix competition for music recommendation. I'm guessing the slides of the tutorial will be online soon. I highly recommend having a look at them ;-)
I only attended the recommendation tutorial, but I've been told the other tutorials were also really well done. Seems like this year's ISMIR is not only the best in terms of number of papers submitted, number of people attending, best location ever, but also best content ever! ;-)
Btw, Paul's blogging about ISMIR in case you haven't noticed yet. And a number of pictures have already been uploaded to flickr tagged ismir2007.
I only attended the recommendation tutorial, but I've been told the other tutorials were also really well done. Seems like this year's ISMIR is not only the best in terms of number of papers submitted, number of people attending, best location ever, but also best content ever! ;-)
Btw, Paul's blogging about ISMIR in case you haven't noticed yet. And a number of pictures have already been uploaded to flickr tagged ismir2007.
Friday, 21 September 2007
The most frequently cited ISMIR paper
I just did a quick Google scholar search to find the most frequently cited ISMIR paper. I'm not sure if I missed any, but it seems the most frequently cited paper is "Mel Frequency Cepstral Coefficients for Music Modeling" (PDF) presented in 2000 by Beth Logan. According to Google scholar it has been cited 127 times as of today. My coauthors and I have cited that paper several times :-)
MFCCs were originally developed in the speech processing community. Back in 2000 it wasn't obvious if the same techniques could just be "copied and pasted" to music information retrieval. MFCCs are now a very standard technique that are being used to compute music similarity, classify genres, identify instruments, segment music, ... In fact, today MFCCs are so common that they are often mentioned in ISMIR papers without citing a source.
MFCCs were originally developed in the speech processing community. Back in 2000 it wasn't obvious if the same techniques could just be "copied and pasted" to music information retrieval. MFCCs are now a very standard technique that are being used to compute music similarity, classify genres, identify instruments, segment music, ... In fact, today MFCCs are so common that they are often mentioned in ISMIR papers without citing a source.
Monday, 17 September 2007
620, 10, 5
Michael Fingerhut announced today on the music-ir list that his complete list of ISMIR papers now contains 620 entries (including this year’s papers). That’s an impressive pile of papers that the ISMIR community has produced since 2000... Btw, there have been only 10 papers so far which contained “recommend” in the title. 5 of those will be presented this year... Given that there will also be a tutorial on recommendation, and that I've mostly been blogging about recommendations recently makes me wonder if recommendations is about to establish itself as one of the core topics of MIR?
Sunday, 26 August 2007
ISMIR: Short List of Papers
I just compiled my short list of papers I don’t want to miss at ISMIR 2007 which starts in about 4 weeks. Of course I’m interested in all papers, but if I run out of time while exploring posters, or need to choose between different sessions, I’ll prefer the ones listed here.
Fuzzy Song Sets for Music Warehouses
To be honest, this is just on the list because given the title I don’t have the slightest clue what this paper is about. I know what fuzzy sets are thanks to Klaas. I’m guessing that a music warehouse is a synonym for a digital library of music. I wonder if the second part of the title got lost?
Music Clustering with Constraints
Another title that puzzles me. Seems like titles have been cut off a lot. They forgot to mention according to what they are clustering the music. Number of musical notes in a piece? AFAIK, most clustering algorithms have some form of constraints. For example, in standard k-means the number of clusters is constrained. When using GMMs it is very common to constrain the minimum variance of an individual Gaussian. Anyway, I’m into clustering algorithms, so this could be an interesting presentation.
Sequence Representation of Music Structure Using Higher-Order Similarity Matrix and Maximum-Likelihood Approach
The author of this one has done lots of interesting stuff in the past. I’m curious what he’s up to this time. Music structure analysis is definitely something very interesting that could be very useful in many ways.
Algorithms for Determining and Labelling Approximate Hierarchical Self-Similarity
Again at least one of the authors has have done very interesting stuff in the past and I’m really interested in music structure analysis.
Transposition-Invariant Self-Similarity Matrices
I’m only guessing but this one could be about self-similarity with respect to melody. (I’m guessing that the previous 2 are focusing on self-similarity with respect to timbre or chroma.) Melodic similarity is a lot harder than timbre similarity. I’m curious how they did it.
A Supervised Approach for Detecting Boundaries in Music Using Difference Features and Boosting
If I miss this presentation I might upset my coauthors ;-)
Automatic Derivation of Musical Structure: A Tool for Research on Schenkerian Analysis
I had to Google Schenkerian. It sounds interesting.
Improving Genre Classification by Combination of Audio and Symbolic Descriptors Using a Transcription System
I’m very curious what kind of symbolic descriptors the authors used. Note density? I’ve seen lots of work on audio-based genre classification, and some work on using MIDI (which is usually referred to as symbolic information, but the authors could also mean something very different with symbolic). I’m pretty sure I’ve read at least one article on the combination of audio and MIDI information, but I don’t think I’ve ever seen anyone actually succeed. I’m curious what results the authors got, and I hope they used an artist filter.
Exploring Mood Metadata: Relationships with Genre, Artist and Usage Metadata
Let me guess: pop is usually happy and upbeat, and death metal is rather aggressive? :-) I wonder though what usage metadata is (if people listen to it while driving their cars, working, jogging etc?).
How Many Beans Make Five? The Consensus Problem in Music-Genre Classification and a New Evaluation Method for Single-Genre Categorisation Systems
Single-category classification? I think I’m good at that ;-) (Yes, I know that with single they mean binary classification.) Anyway, I’m curious what the authors say about genre classification and consensus. The authors probably have a very different perspective than I do.
Bayesian Aggregation for Hierarchical Genre Classification
I hope they either compare it to existing techniques, or use evaluation DBs that have been used previously. And I hope they used an artist filter. I’m very curious though what they aggregated.
Finding New Music: A Diary Study of Everyday Encounters with Novel Songs
If I had a very, very short list of papers I wouldn’t want to miss, than this would be on it :-)
Improving Efficiency and Scalability of Model-Based Music Recommender System Based on Incremental Training
Made in Japan, what else is there left to say? ;-)
This would also be on the very, very short list of presentations I wouldn’t want to miss.
Virtual Communities for Creating Shared Music Channels
I’m guessing that this could be really interesting, but I wish the title was more specific. Under the same title one could present, for example, how Last.fm groups and their group radio stations work, or how people get together on Last.fm to tag music to create their own radio stations.
MusicSun: A New Approach to Artist Recommendation
Another title that’s missing lots of information, nevertheless, I won’t skip this one.
Evaluation of Distance Measures Between Gaussian Mixture Models of MFCCs
I’m curious which approaches they tested and how and what their conclusions are.
An Analysis of the Mongeau-Sankoff Algorithm for Music Information Retrieval
Another title that sent me to Google. This time there were only 15 results, none of which did a good job in explaining it to me. Anyway it has MIR in the title, so I think I should have a look.
Assessment of Perceptual Music Similarity
Sounds like a follow-up of the work they presented last year. I’m very curious. I hope they got more than 2 pages in the proceedings. I’d love to read more on this topic.
jWebMiner: A Web-Based Feature Extractor
Sounds like there’s more great software from McGill for everyone to use.
Meaningfully Browsing Music Services
I’ve seen a demo that included Last.fm, so I really can’t miss this one.
Web-Based Detection of Music Band Members and Line-Up
Personally I would be tempted to just use MusicBrainz DB for that. I wonder how much more data the authors could find by crawling the web in general.
Tool Play Live: Dealing with Ambiguity in Artist Similarity Mining from the Web
Artist name ambiguity is an interesting problem, I wonder what solution they are presenting.
Keyword Generation for Lyrics
I’m guessing these are keywords that summarize the lyrics? I wonder if they use some abstraction as well to classify, for example, a song as a love song.
MIR in Matlab (II): A Toolbox for Musical Feature Extraction from Audio
I use Matlab everyday and I don’t think I’ve heard of this toolbox before, sounds interesting.
A Demonstration of the SyncPlayer System
I think I saw a demo of this at the MIREX meeting in Vienna. If I remember correctly the synchronization refers mainly to synchronizing lyrics with the audio but it can do lots of other cool stuff, too.
Performance of Philips Audio Fingerprinting under Desynchronisation
I have no clue what desynchronisation is, but I know that fingerprinting is relevant to what I work on.
Robust Music Identification, Detection, and Analysis
This could be another paper on fingerprinting?
Audio Identification Using Sinusoidal Modeling and Application to Jingle Detection
More fingerprinting fun.
Audio Fingerprint Identification by Approximate String Matching
Seems like fingerprinting has established itself as a research direction again :-)
Musical Memory of the World –- Data Infrastructure in Ethnomusicological Archives
It’s not directly related to my own work, but sounds very interesting.
Globe of Music - Music Library Visualization Using Geosom
A visualization of a music library using a metaphor of geographic maps? I’m curious how using a globe improves the experience.
Strike-A-Tune: Fuzzy Music Navigation Using a Drum Interface
I hope they’ll let me have a try :-)
Using 3D Visualizations to Explore and Discover Music
I believe I’ve seen this demo already, but I never got to try it out myself. I hope the waiting line won’t be too long.
Music Browsing Using a Tabletop Display
If the demo is interesting I’ll forgive them their not very informative title ;-)
Search&Select -– Intuitively Retrieving Music from Large Collections
I like the authors work. I’m very curious what he built this time.
Ensemble Learning for Hybrid Music Recommendation
It has the words music recommendation in the title, and the authors have done some interesting work in the past.
Music Recommendation Mapping and Interface Based on Structural Network Entropy
Another music recommendation paper, I’m guessing this one is about a certain MyStrand visualization. I’m particularly interested in the “structural network entropy” part.
Influence of Tempo and Subjective Rating of Music in Step Frequency of Running
My guess is that tempo has an impact and that this impact is even higher for music I like? But I wouldn’t expect the subjective rating to have a very high impact. I often notice how I start walking to the beats of music I hear even if I don’t like the music.
Sociology and Music Recommendation Systems
Another paper I’d put on the very, very short list :-)
Visualizing Music: Tonal Progressions and Distributions
Sounds great! I should check if they already have some videos online.
Localized Key Finding from Audio Using Nonnegative Matrix Factorization for Segmentation
I’m curious how the author used a nonnegative matrix factorization for this task. I’ve never used one, but I thought they are usually used for mixtures. However, segments (like chorus and instrument solos) are usually not best described as mixtures?
Invited Talk
Sounds like I’ll learn interesting things about copyright, creative commons, and other intellectual property issues involved in music information retrieval.
Audio-Based Cover Song Retrieval Using Approximate Chord Sequences: Testing Shifts, Gaps, Swaps and Beats
I mainly want to know what the author has been up to, but I’m also interested in cover song detection.
Polyphonic Instrument Recognition Using Spectral Clustering
I want to see this one too, but it’s at the same time as the previous paper. The papers use rather similar techniques and deal with rather similar problems. I don’t understand why they were put up to compete with each other. Something non-audio related would have been a much better counter part.
Supervised and Unsupervised Sequence Modelling for Drum Transcription
I wonder how good their drum transcription works. I hope they have lots of demos.
A Unified System for Chord Transcription and Key Extraction Using Hidden Markov Models
Again a paper I really don’t want to miss but it’s at the same time as the one above. There are so many papers that don’t deal with extracting interesting information from audio signals that I absolutely don’t understand why they arranged this parallel session the way they did.
Combining Temporal and Spectral Features in HMM-Based Drum Transcription
I’m not sure if I’ll check out this one or the one below. Both are really interesting.
A Cross-Validated Study of Modelling Strategies for Automatic Chord Recognition in Audio
Sounds like they might have some interesting results.
Improving the Classification of Percussive Sounds with Analytical Features: A Case Study
I must see this one because I recently did some work on drum sounds. I’m curious if the authors include all sorts of percussive instruments (such as a piano) or if it’s drums mainly.
Discovering Chord Idioms Through Beatles and Real Book Songs
I’d love to see this one, too :-(
Don’t get me wrong: I fully support parallel sessions (there isn’t really an alternative given this many oral presentations) but unfortunately the sessions weren’t split in a way that would allow me to see everything I would like to see. Why not put chords and alignment parallel to each other?? To demonstrate my point I won’t list any papers of the alignment session.
Automatic Instrument Recognition in a Polyphonic Mixture Using Sparse Representations
Another strange thing about how the sessions were split is that one parallel session always ends 15 minutes earlier than the other one. Do the organizers expect that everyone from the other session runs to the other session? I’d prefer if all sessions would end at the same time and thus make it easier to find a group to go join for lunch. Anyway, sounds like an interesting paper.
ATTA: Implementing GTTM on a Computer
It’s been a while since I first heard a presentation on GTTM. I guess it’s about time to refresh my knowledge.
An Experiment on the Role of Pitch Intervals in Melodic Segmentation
I have no clue… but segments often have different “local keys”. The chords within keys are usually clearly defined. Each chord has specific pitch intervals… I wonder what experiment they did.
Vivo - Visualizing Harmonic Progressions and Voice-Leading in PWGL
A visualization!
Visualizing Music on the Metrical Circle
Another visualization :-)
Applying Rhythmic Similarity Based on Inner Metric Analysis to Folksong Research
I’m curious how they compute rhythmic similarity. I have seen a lot of work on extracting rhythm information, but haven’t seen much on computing similarities using it.
Music Retrieval by Rhythmic Similarity Applied on Greek and African Traditional Music
Another rhythmic similarity paper :-)
A Dynamic Programming Approach to the Extraction of Phrase Boundaries from Tempo Variations in Expressive Performances
A long time ago I did some work on segmenting tempo variations… I’m curious how they represent tempo (do they apply temporal smoothing?) and how well detecting phrase boundaries works given only tempo. (Why not use loudness as well?)
Creating a Simplified Music Mood Classification Ground-Truth Set
Sounds like this might also be related to the MIREX mood classification task.
Assessment of State-of-the-Art Meter Analysis Systems with an Extended Meter Description Model
I wonder how good state-of-the-art methods work for meter detection.
Evaluating a Chord-Labelling Algorithm
Chord detection is great.
A Qualitative Assessment of Measures for the Evaluation of a Cover Song Identification System
Cover song detection is great, too.
The Music Information Retrieval Evaluation Exchange “Do-It-Yourself” Web Service
Wow! I wonder if they will have a demo ready?
Preliminary Analyses of Information Features Provided by Users for Identifying Music
I have no clue what this one is about, but it’s probably MIREX related.
Finding Music in Scholarly Sets and Series: The Index to Printed Music (IPM)
One of the many things I know nothing about, but it sounds interesting.
Humming on Audio Databases
I wonder if they provide a demo, and if they can motivate people to use it. (It will probably be more fun listening to people sing than see if their system works.)
A Query by Humming System that Learns from Experience
Would be nice to have this one right next to the previous one.
Classifying Music Audio with Timbral and Chroma Features
Another one for the very, very short list. I’m curious how the author combined the features, and if he measured improvements, and if he did artist identification or genre classification (and if he used an artist filter if so).
A Closer Look on Artist Filters for Musical Genre Classification
Sounds like something everyone should be using :-)
A Demonstrator for Automatic Music Mood Estimation
I definitely want to see this demonstration.
Mood-ex-Machina: Towards Automation of Moody Tunes
I wonder what this sounds like.
Pedagogical Transcription for Multimodal Sitar Performance
I wonder if it’s so pedagogical that I can understand it?
Drum Transcription in Polyphonic Music Using Non-Negative Matrix Factorisation
Not sure what’s new here, but I’ll be there to find out.
Tuning Frequency Estimation Using Circular Statistics
No clue what this is about. My best guess would be that it’s related to the pitch corrections I’ve seen in chord transcription systems.
TagATune: A Game for Music and Sound Annotation
Wow another music game! I haven’t heard of this one yet and Google hasn’t either. I’m very curious how it differs from the Listen Game and the MajorMinor game.
A Web-Based Game for Collecting Music Metadata
Would be great if they publish some usage statistics.
Autotagging Music Using Supervised Machine Learning
I’m very curious what results they got.
A Stochastic Representation of the Dynamics of Sung Melody
Another Japanese production :-)
Singing Melody Extraction in Polyphonic Music by Harmonic Tracking
I wonder how high the improvements were by tracking the harmony.
Singer Identification in Polyphonic Music Using Vocal Separation and Pattern Recognition Methods
I wonder how they evaluated this. Did all singers have the same background instruments and sing in the same musical style?
Transcription and Multipitch Estimation Session
I know nothing about multipitch estimation. But I hope to hear some nice demonstrations in the session.
Identifying Words that are Musically Meaningful
I wonder what the most musically meaningful word is. At Last.fm I think it’s “rock”. Another word very high up in the Last.fm ranks is “chillout” :-)
A Semantic Space for Music Derived from Social Tags
I’m curious what their tag space looks like.
The Music Ontology
I don’t know much about ontologies, but it sounds like this is the one and only one for music, so I better not miss it.
Signal + Context = Better Classification
I love this title. I hope the first author will be presenting it.
A Music Information Retrieval System Based on Singing Voice Timbre
I’ll probably be totally exhausted from having seen so many presentations and posters by this time, but I’ll try to reserve some energy to be able to concentrate on this talk.
Poster session 3 (MIREX)
Usually one of the highlights at ISMIR. I hope the MIREX teams manages to have the results ready in time. Only about 4 weeks left to get everything done.
Methodological Considerations in Studies of Musical Similarity
I wish this paper would have been published before I wrote my thesis. But I guess it's never too late to learn :-)
Similarity Based on Rating Data
Sounds like something Last.fm has been doing since years: The ratings are measured based on how often people listen to a song. Then standard collaborative filtering techniques are applied. The results are not too bad. I’m guessing that the authors used very sparse data compared to the data Last.fm has. Another paper I’d put on my very, very short list.
A Study on Attribute-Based Taxonomy for Music Information Retrieval
I wonder if this is similar to Pandora’s music genome project?
Variable-Size Gaussian Mixture Models for Music Similarity Measures
I wonder if and how the author was able to measure significant improvements.
Towards Integration of MIR and Folk Song Research
I like folk music, and I like MIR.
From Rhythm Patterns to Perceived Tempo
I’m curious how they approach this. A rhythm pattern (as defined in music books) does (AFAIK) not have any tempo information and can be played at different tempi. But I’m sure this is an interesting paper :-)
The Quest for Ground Truth in Musical Artist Tagging in the Social Web Era
The title reminds me of one of the more important papers in the short history of ISMIR. Tags are something very subjective, there is no right or wrong. You’ll always find people complaining about how other people mistagged the genre of a song. It will be interesting to see if this paper has the potential to join the ranks of the original ISMIR paper with a similar title.
Annotating Music Collections: How Content-Based Similarity Helps to Propagate Labels
Sounds like something very useful.
A Game-Based Approach for Collecting Semantic Annotations of Music
I hope they’ll present some usage statistics.
Human Similarity Judgments: Implications for the Design of Formal Evaluations
I wonder why this paper isn’t presented before the MIREX panel. Seems like it might contain a lot of information that would be useful for the discussion.
Fuzzy Song Sets for Music Warehouses
To be honest, this is just on the list because given the title I don’t have the slightest clue what this paper is about. I know what fuzzy sets are thanks to Klaas. I’m guessing that a music warehouse is a synonym for a digital library of music. I wonder if the second part of the title got lost?
Music Clustering with Constraints
Another title that puzzles me. Seems like titles have been cut off a lot. They forgot to mention according to what they are clustering the music. Number of musical notes in a piece? AFAIK, most clustering algorithms have some form of constraints. For example, in standard k-means the number of clusters is constrained. When using GMMs it is very common to constrain the minimum variance of an individual Gaussian. Anyway, I’m into clustering algorithms, so this could be an interesting presentation.
Sequence Representation of Music Structure Using Higher-Order Similarity Matrix and Maximum-Likelihood Approach
The author of this one has done lots of interesting stuff in the past. I’m curious what he’s up to this time. Music structure analysis is definitely something very interesting that could be very useful in many ways.
Algorithms for Determining and Labelling Approximate Hierarchical Self-Similarity
Again at least one of the authors has have done very interesting stuff in the past and I’m really interested in music structure analysis.
Transposition-Invariant Self-Similarity Matrices
I’m only guessing but this one could be about self-similarity with respect to melody. (I’m guessing that the previous 2 are focusing on self-similarity with respect to timbre or chroma.) Melodic similarity is a lot harder than timbre similarity. I’m curious how they did it.
A Supervised Approach for Detecting Boundaries in Music Using Difference Features and Boosting
If I miss this presentation I might upset my coauthors ;-)
Automatic Derivation of Musical Structure: A Tool for Research on Schenkerian Analysis
I had to Google Schenkerian. It sounds interesting.
Improving Genre Classification by Combination of Audio and Symbolic Descriptors Using a Transcription System
I’m very curious what kind of symbolic descriptors the authors used. Note density? I’ve seen lots of work on audio-based genre classification, and some work on using MIDI (which is usually referred to as symbolic information, but the authors could also mean something very different with symbolic). I’m pretty sure I’ve read at least one article on the combination of audio and MIDI information, but I don’t think I’ve ever seen anyone actually succeed. I’m curious what results the authors got, and I hope they used an artist filter.
Exploring Mood Metadata: Relationships with Genre, Artist and Usage Metadata
Let me guess: pop is usually happy and upbeat, and death metal is rather aggressive? :-) I wonder though what usage metadata is (if people listen to it while driving their cars, working, jogging etc?).
How Many Beans Make Five? The Consensus Problem in Music-Genre Classification and a New Evaluation Method for Single-Genre Categorisation Systems
Single-category classification? I think I’m good at that ;-) (Yes, I know that with single they mean binary classification.) Anyway, I’m curious what the authors say about genre classification and consensus. The authors probably have a very different perspective than I do.
Bayesian Aggregation for Hierarchical Genre Classification
I hope they either compare it to existing techniques, or use evaluation DBs that have been used previously. And I hope they used an artist filter. I’m very curious though what they aggregated.
Finding New Music: A Diary Study of Everyday Encounters with Novel Songs
If I had a very, very short list of papers I wouldn’t want to miss, than this would be on it :-)
Improving Efficiency and Scalability of Model-Based Music Recommender System Based on Incremental Training
Made in Japan, what else is there left to say? ;-)
This would also be on the very, very short list of presentations I wouldn’t want to miss.
Virtual Communities for Creating Shared Music Channels
I’m guessing that this could be really interesting, but I wish the title was more specific. Under the same title one could present, for example, how Last.fm groups and their group radio stations work, or how people get together on Last.fm to tag music to create their own radio stations.
MusicSun: A New Approach to Artist Recommendation
Another title that’s missing lots of information, nevertheless, I won’t skip this one.
Evaluation of Distance Measures Between Gaussian Mixture Models of MFCCs
I’m curious which approaches they tested and how and what their conclusions are.
An Analysis of the Mongeau-Sankoff Algorithm for Music Information Retrieval
Another title that sent me to Google. This time there were only 15 results, none of which did a good job in explaining it to me. Anyway it has MIR in the title, so I think I should have a look.
Assessment of Perceptual Music Similarity
Sounds like a follow-up of the work they presented last year. I’m very curious. I hope they got more than 2 pages in the proceedings. I’d love to read more on this topic.
jWebMiner: A Web-Based Feature Extractor
Sounds like there’s more great software from McGill for everyone to use.
Meaningfully Browsing Music Services
I’ve seen a demo that included Last.fm, so I really can’t miss this one.
Web-Based Detection of Music Band Members and Line-Up
Personally I would be tempted to just use MusicBrainz DB for that. I wonder how much more data the authors could find by crawling the web in general.
Tool Play Live: Dealing with Ambiguity in Artist Similarity Mining from the Web
Artist name ambiguity is an interesting problem, I wonder what solution they are presenting.
Keyword Generation for Lyrics
I’m guessing these are keywords that summarize the lyrics? I wonder if they use some abstraction as well to classify, for example, a song as a love song.
MIR in Matlab (II): A Toolbox for Musical Feature Extraction from Audio
I use Matlab everyday and I don’t think I’ve heard of this toolbox before, sounds interesting.
A Demonstration of the SyncPlayer System
I think I saw a demo of this at the MIREX meeting in Vienna. If I remember correctly the synchronization refers mainly to synchronizing lyrics with the audio but it can do lots of other cool stuff, too.
Performance of Philips Audio Fingerprinting under Desynchronisation
I have no clue what desynchronisation is, but I know that fingerprinting is relevant to what I work on.
Robust Music Identification, Detection, and Analysis
This could be another paper on fingerprinting?
Audio Identification Using Sinusoidal Modeling and Application to Jingle Detection
More fingerprinting fun.
Audio Fingerprint Identification by Approximate String Matching
Seems like fingerprinting has established itself as a research direction again :-)
Musical Memory of the World –- Data Infrastructure in Ethnomusicological Archives
It’s not directly related to my own work, but sounds very interesting.
Globe of Music - Music Library Visualization Using Geosom
A visualization of a music library using a metaphor of geographic maps? I’m curious how using a globe improves the experience.
Strike-A-Tune: Fuzzy Music Navigation Using a Drum Interface
I hope they’ll let me have a try :-)
Using 3D Visualizations to Explore and Discover Music
I believe I’ve seen this demo already, but I never got to try it out myself. I hope the waiting line won’t be too long.
Music Browsing Using a Tabletop Display
If the demo is interesting I’ll forgive them their not very informative title ;-)
Search&Select -– Intuitively Retrieving Music from Large Collections
I like the authors work. I’m very curious what he built this time.
Ensemble Learning for Hybrid Music Recommendation
It has the words music recommendation in the title, and the authors have done some interesting work in the past.
Music Recommendation Mapping and Interface Based on Structural Network Entropy
Another music recommendation paper, I’m guessing this one is about a certain MyStrand visualization. I’m particularly interested in the “structural network entropy” part.
Influence of Tempo and Subjective Rating of Music in Step Frequency of Running
My guess is that tempo has an impact and that this impact is even higher for music I like? But I wouldn’t expect the subjective rating to have a very high impact. I often notice how I start walking to the beats of music I hear even if I don’t like the music.
Sociology and Music Recommendation Systems
Another paper I’d put on the very, very short list :-)
Visualizing Music: Tonal Progressions and Distributions
Sounds great! I should check if they already have some videos online.
Localized Key Finding from Audio Using Nonnegative Matrix Factorization for Segmentation
I’m curious how the author used a nonnegative matrix factorization for this task. I’ve never used one, but I thought they are usually used for mixtures. However, segments (like chorus and instrument solos) are usually not best described as mixtures?
Invited Talk
Sounds like I’ll learn interesting things about copyright, creative commons, and other intellectual property issues involved in music information retrieval.
Audio-Based Cover Song Retrieval Using Approximate Chord Sequences: Testing Shifts, Gaps, Swaps and Beats
I mainly want to know what the author has been up to, but I’m also interested in cover song detection.
Polyphonic Instrument Recognition Using Spectral Clustering
I want to see this one too, but it’s at the same time as the previous paper. The papers use rather similar techniques and deal with rather similar problems. I don’t understand why they were put up to compete with each other. Something non-audio related would have been a much better counter part.
Supervised and Unsupervised Sequence Modelling for Drum Transcription
I wonder how good their drum transcription works. I hope they have lots of demos.
A Unified System for Chord Transcription and Key Extraction Using Hidden Markov Models
Again a paper I really don’t want to miss but it’s at the same time as the one above. There are so many papers that don’t deal with extracting interesting information from audio signals that I absolutely don’t understand why they arranged this parallel session the way they did.
Combining Temporal and Spectral Features in HMM-Based Drum Transcription
I’m not sure if I’ll check out this one or the one below. Both are really interesting.
A Cross-Validated Study of Modelling Strategies for Automatic Chord Recognition in Audio
Sounds like they might have some interesting results.
Improving the Classification of Percussive Sounds with Analytical Features: A Case Study
I must see this one because I recently did some work on drum sounds. I’m curious if the authors include all sorts of percussive instruments (such as a piano) or if it’s drums mainly.
Discovering Chord Idioms Through Beatles and Real Book Songs
I’d love to see this one, too :-(
Don’t get me wrong: I fully support parallel sessions (there isn’t really an alternative given this many oral presentations) but unfortunately the sessions weren’t split in a way that would allow me to see everything I would like to see. Why not put chords and alignment parallel to each other?? To demonstrate my point I won’t list any papers of the alignment session.
Automatic Instrument Recognition in a Polyphonic Mixture Using Sparse Representations
Another strange thing about how the sessions were split is that one parallel session always ends 15 minutes earlier than the other one. Do the organizers expect that everyone from the other session runs to the other session? I’d prefer if all sessions would end at the same time and thus make it easier to find a group to go join for lunch. Anyway, sounds like an interesting paper.
ATTA: Implementing GTTM on a Computer
It’s been a while since I first heard a presentation on GTTM. I guess it’s about time to refresh my knowledge.
An Experiment on the Role of Pitch Intervals in Melodic Segmentation
I have no clue… but segments often have different “local keys”. The chords within keys are usually clearly defined. Each chord has specific pitch intervals… I wonder what experiment they did.
Vivo - Visualizing Harmonic Progressions and Voice-Leading in PWGL
A visualization!
Visualizing Music on the Metrical Circle
Another visualization :-)
Applying Rhythmic Similarity Based on Inner Metric Analysis to Folksong Research
I’m curious how they compute rhythmic similarity. I have seen a lot of work on extracting rhythm information, but haven’t seen much on computing similarities using it.
Music Retrieval by Rhythmic Similarity Applied on Greek and African Traditional Music
Another rhythmic similarity paper :-)
A Dynamic Programming Approach to the Extraction of Phrase Boundaries from Tempo Variations in Expressive Performances
A long time ago I did some work on segmenting tempo variations… I’m curious how they represent tempo (do they apply temporal smoothing?) and how well detecting phrase boundaries works given only tempo. (Why not use loudness as well?)
Creating a Simplified Music Mood Classification Ground-Truth Set
Sounds like this might also be related to the MIREX mood classification task.
Assessment of State-of-the-Art Meter Analysis Systems with an Extended Meter Description Model
I wonder how good state-of-the-art methods work for meter detection.
Evaluating a Chord-Labelling Algorithm
Chord detection is great.
A Qualitative Assessment of Measures for the Evaluation of a Cover Song Identification System
Cover song detection is great, too.
The Music Information Retrieval Evaluation Exchange “Do-It-Yourself” Web Service
Wow! I wonder if they will have a demo ready?
Preliminary Analyses of Information Features Provided by Users for Identifying Music
I have no clue what this one is about, but it’s probably MIREX related.
Finding Music in Scholarly Sets and Series: The Index to Printed Music (IPM)
One of the many things I know nothing about, but it sounds interesting.
Humming on Audio Databases
I wonder if they provide a demo, and if they can motivate people to use it. (It will probably be more fun listening to people sing than see if their system works.)
A Query by Humming System that Learns from Experience
Would be nice to have this one right next to the previous one.
Classifying Music Audio with Timbral and Chroma Features
Another one for the very, very short list. I’m curious how the author combined the features, and if he measured improvements, and if he did artist identification or genre classification (and if he used an artist filter if so).
A Closer Look on Artist Filters for Musical Genre Classification
Sounds like something everyone should be using :-)
A Demonstrator for Automatic Music Mood Estimation
I definitely want to see this demonstration.
Mood-ex-Machina: Towards Automation of Moody Tunes
I wonder what this sounds like.
Pedagogical Transcription for Multimodal Sitar Performance
I wonder if it’s so pedagogical that I can understand it?
Drum Transcription in Polyphonic Music Using Non-Negative Matrix Factorisation
Not sure what’s new here, but I’ll be there to find out.
Tuning Frequency Estimation Using Circular Statistics
No clue what this is about. My best guess would be that it’s related to the pitch corrections I’ve seen in chord transcription systems.
TagATune: A Game for Music and Sound Annotation
Wow another music game! I haven’t heard of this one yet and Google hasn’t either. I’m very curious how it differs from the Listen Game and the MajorMinor game.
A Web-Based Game for Collecting Music Metadata
Would be great if they publish some usage statistics.
Autotagging Music Using Supervised Machine Learning
I’m very curious what results they got.
A Stochastic Representation of the Dynamics of Sung Melody
Another Japanese production :-)
Singing Melody Extraction in Polyphonic Music by Harmonic Tracking
I wonder how high the improvements were by tracking the harmony.
Singer Identification in Polyphonic Music Using Vocal Separation and Pattern Recognition Methods
I wonder how they evaluated this. Did all singers have the same background instruments and sing in the same musical style?
Transcription and Multipitch Estimation Session
I know nothing about multipitch estimation. But I hope to hear some nice demonstrations in the session.
Identifying Words that are Musically Meaningful
I wonder what the most musically meaningful word is. At Last.fm I think it’s “rock”. Another word very high up in the Last.fm ranks is “chillout” :-)
A Semantic Space for Music Derived from Social Tags
I’m curious what their tag space looks like.
The Music Ontology
I don’t know much about ontologies, but it sounds like this is the one and only one for music, so I better not miss it.
Signal + Context = Better Classification
I love this title. I hope the first author will be presenting it.
A Music Information Retrieval System Based on Singing Voice Timbre
I’ll probably be totally exhausted from having seen so many presentations and posters by this time, but I’ll try to reserve some energy to be able to concentrate on this talk.
Poster session 3 (MIREX)
Usually one of the highlights at ISMIR. I hope the MIREX teams manages to have the results ready in time. Only about 4 weeks left to get everything done.
Methodological Considerations in Studies of Musical Similarity
I wish this paper would have been published before I wrote my thesis. But I guess it's never too late to learn :-)
Similarity Based on Rating Data
Sounds like something Last.fm has been doing since years: The ratings are measured based on how often people listen to a song. Then standard collaborative filtering techniques are applied. The results are not too bad. I’m guessing that the authors used very sparse data compared to the data Last.fm has. Another paper I’d put on my very, very short list.
A Study on Attribute-Based Taxonomy for Music Information Retrieval
I wonder if this is similar to Pandora’s music genome project?
Variable-Size Gaussian Mixture Models for Music Similarity Measures
I wonder if and how the author was able to measure significant improvements.
Towards Integration of MIR and Folk Song Research
I like folk music, and I like MIR.
From Rhythm Patterns to Perceived Tempo
I’m curious how they approach this. A rhythm pattern (as defined in music books) does (AFAIK) not have any tempo information and can be played at different tempi. But I’m sure this is an interesting paper :-)
The Quest for Ground Truth in Musical Artist Tagging in the Social Web Era
The title reminds me of one of the more important papers in the short history of ISMIR. Tags are something very subjective, there is no right or wrong. You’ll always find people complaining about how other people mistagged the genre of a song. It will be interesting to see if this paper has the potential to join the ranks of the original ISMIR paper with a similar title.
Annotating Music Collections: How Content-Based Similarity Helps to Propagate Labels
Sounds like something very useful.
A Game-Based Approach for Collecting Semantic Annotations of Music
I hope they’ll present some usage statistics.
Human Similarity Judgments: Implications for the Design of Formal Evaluations
I wonder why this paper isn’t presented before the MIREX panel. Seems like it might contain a lot of information that would be useful for the discussion.
Sunday, 29 July 2007
ISMIR 8.0
Paris in 2002, Barcelona in 2004, London in 2005, and now finally Vienna! For the fourth time in its history the International Sconference on Music Information Retrieval (ISMIR) will be held in Europe. Needless to say that ISMIR in Vienna will be the best ever. Following a new all time high in the number of submitted papers rumors are quickly spreading that tickets are already almost sold out (just like in London 2005). Seems like everyone wanted to get the early registration bonus (which ends on the 31st of July). It also seems like two of my Last.fm colleagues and I have been lucky enough to grab some of the last tickets for the highly anticipated tutorial on music recommendation given by Paul Lamere and Oscar Celma. However, the other three tutorials are just as exciting, I wouldn’t be surprised if the organizers will need to find bigger lecture rooms.
There are so many reasons why ISMIR in Vienna will be the best ever that I could spend the rest of my life writing them down. Two of the main reasons are that it’s the right place and the right time.
It’s the right place because Vienna is the most beautiful city in the world with the highest living standards (and yet affordable prices). Vienna has a rich history in music, and Vienna is located in the heart of Europe which is currently one of the leading forces in music information retrieval research.
It’s the right time because music information retrieval has never been more exciting. The whole music industry is just about to undergo massive transformations driven by technological changes. Music consumption habits of the younger generation have already changed drastically, and music is surrounding us like never before.
> Join the ISMIR 2007 group on Facebook here.
> Read about ISMIR 2007 on Paul’s blog here and here.
There are so many reasons why ISMIR in Vienna will be the best ever that I could spend the rest of my life writing them down. Two of the main reasons are that it’s the right place and the right time.
It’s the right place because Vienna is the most beautiful city in the world with the highest living standards (and yet affordable prices). Vienna has a rich history in music, and Vienna is located in the heart of Europe which is currently one of the leading forces in music information retrieval research.
It’s the right time because music information retrieval has never been more exciting. The whole music industry is just about to undergo massive transformations driven by technological changes. Music consumption habits of the younger generation have already changed drastically, and music is surrounding us like never before.
> Join the ISMIR 2007 group on Facebook here.
> Read about ISMIR 2007 on Paul’s blog here and here.
Saturday, 19 May 2007
ISMIR Reviewing
The ISMIR review deadline is on Monday. On the website they have a nice list showing how much of their work the reviewers have already completed. Next to each reviewer's name there are some smilies (see picture on the right). I got all of mine done, so I got 3 smiles. There are still a large number of reviewers who seem to be waiting until the last moment before submitting their reviews. I hope the acceptance notification is not delayed because of them.My impression from the papers that I reviewed is that some authors don't seem very concerned about evaluations. In some areas there are currently so many papers that it is impossible to really read all of them. If a paper doesn't offer an evaluation that helps understand how it relates to previous work (and there is lots of previous work on the topics I've reviewed) then I have a very hard time motivating myself to read it :-/
Wednesday, 18 April 2007
Squeezing an ISMIR Paper
The last days I've spent fighting Latex. Trying to squeeze as much unnecessary space as possible out of ISMIR papers. (Of course I've also been shortening the contents, but I've reached the point where I really don't feel like deleting/shortening any more paragraphs.) Btw, did you know, that you can fit about 25 references into half a page? Right now I'm debating if a baseline stretch of 0.97 is too low. I can't really tell the difference when looking at a paragraph, but overall the paper is 1/4 page shorter :-)
Friday, 23 March 2007
ISMIR Steering Committee
ISMIR is by far my most favorite conference. I've attended all ISMIRs since 2002. My research has been revolving all around the ISMIR community, I've learned a lot from ISMIR papers (Btw, most papers I cite are ISMIR papers), I learned a lot from conversations I had at ISMIR, I got my current job through ISMIR, and even my next job... but only recently I discovered the ISMIR steering committee.
Now that I discovered it, I realize that many people that seem really important to me in the community are not included. Which seems a bit odd. In particular, I wonder why none of the following people are included: (in alphabetical order)
I should probably mention that I didn't ask any of the people I'm listing here. So some (or most of them?) might not even want to or might not have the time to be on the committee (which might explain why they aren't right now?) And I'd also like to add that this is only a very short list. There are many more I think would be very suitable to be on the committee (Andreas Rauber, Michael Casey, Simon Dixon, ...) but I felt the list was getting a bit long.
I wonder how new members get added to the committee? Can I just post some suggestions on the music-ir list? Is there a limit on the size of the committee? What about some form of society? I think Michael Fingerhut once mentioned that ISMIR could stand for the "international society of music information retrieval". That would be wonderful.
Now that I discovered it, I realize that many people that seem really important to me in the community are not included. Which seems a bit odd. In particular, I wonder why none of the following people are included: (in alphabetical order)
Anssi Klapuri
Has done some amazing research, has been very active in the community, helping many others. Has given many interesting talks, got involved in evaluation efforts like MIREX...
Dan Ellis
Another person everyone knows, great research, very active, in particular when it comes to evaluation. Has shared a lot of data, code, has written many frequently cited papers, ...
Francois Pachet
I guess I don't need to mention anything here? Has pioneered many very interesting research directions, is always happy to discuss research topics, inspirational, ...
George Tzanetakis
Another legend... also co-organizer of ISMIR last year. He gave us Marsyas, many great papers, and genre classification.
Gerhard Widmer
Co-organizer of ISMIR this year. He was my PhD supervisor, so I might be biased. But even if I look at this entirely objectively, I'd definitely vote for him being on the committee.
Mark Sandler
Co-organizer of ISMIR in London. Runs a great (and very large and growing) team of music researchers in London. Involved in some amazing MIR related projects...
Masataka Goto
Again I might be biased because I'm working with him right now. But the same applies as in Gerhard's case. Furthermore, having him in the committee would bring the Japanese MIR community closer to the international one.
Paul Lamere
Paul has been very active in the MIR community, attended the last ISMIR conferences, writes a great blog covering lots of MIR topics. Furthermore, he has a great overview of MIR topics outside of academia ...
Xavier Serra
Organizer of ISMIR 2004. Also legendary in the MIR community. Well known for his ground breaking PhD thesis and for being an excellent manager.
Has done some amazing research, has been very active in the community, helping many others. Has given many interesting talks, got involved in evaluation efforts like MIREX...
Dan Ellis
Another person everyone knows, great research, very active, in particular when it comes to evaluation. Has shared a lot of data, code, has written many frequently cited papers, ...
Francois Pachet
I guess I don't need to mention anything here? Has pioneered many very interesting research directions, is always happy to discuss research topics, inspirational, ...
George Tzanetakis
Another legend... also co-organizer of ISMIR last year. He gave us Marsyas, many great papers, and genre classification.
Gerhard Widmer
Co-organizer of ISMIR this year. He was my PhD supervisor, so I might be biased. But even if I look at this entirely objectively, I'd definitely vote for him being on the committee.
Mark Sandler
Co-organizer of ISMIR in London. Runs a great (and very large and growing) team of music researchers in London. Involved in some amazing MIR related projects...
Masataka Goto
Again I might be biased because I'm working with him right now. But the same applies as in Gerhard's case. Furthermore, having him in the committee would bring the Japanese MIR community closer to the international one.
Paul Lamere
Paul has been very active in the MIR community, attended the last ISMIR conferences, writes a great blog covering lots of MIR topics. Furthermore, he has a great overview of MIR topics outside of academia ...
Xavier Serra
Organizer of ISMIR 2004. Also legendary in the MIR community. Well known for his ground breaking PhD thesis and for being an excellent manager.
I should probably mention that I didn't ask any of the people I'm listing here. So some (or most of them?) might not even want to or might not have the time to be on the committee (which might explain why they aren't right now?) And I'd also like to add that this is only a very short list. There are many more I think would be very suitable to be on the committee (Andreas Rauber, Michael Casey, Simon Dixon, ...) but I felt the list was getting a bit long.
I wonder how new members get added to the committee? Can I just post some suggestions on the music-ir list? Is there a limit on the size of the committee? What about some form of society? I think Michael Fingerhut once mentioned that ISMIR could stand for the "international society of music information retrieval". That would be wonderful.
Subscribe to:
Posts (Atom)