The State of the Art in Music Information Retrieval
The proceedings for ISMIR 2005
have been posted, so if you didn't make it to this year's Music
Information Retrieval conference you can do the next best thing and
read all the papers. There's quite a range of topics including user
studies, audio classification, symbolic classification, toolsets.
A good place to start is A Survey of Music Information Retrieval Systems a survey paper describing the various content-based music information retrieval systems.
For the hard-core math weenies out there, the paper that seems to have the highest density of equations to text is
the paper Harmonic-Temporal Clustering via Deterministic Annealing EM Algorithm for Audio Feature Extraction by Hirokazu Kameoka and friends with 35 labeled equations (one equation consumes nearly half a page of text).
The paper by Charles Parker called Applications of Binary Classification and Adaptive Boosting to the Query-By-Humming Problem is a quite well written paper describing methods of symbolic alignment using binary classifiers. (I tend to favor papers that rely on pseudocode to explain things as opposed to maths, which is Mr. Parker's approach).
Foafing the Music: A Music Recommendation System based on RSS Feeds and User Preferences is a MIR meets Web 2.0 paper with lots of good ideas about combining the various source of music information such as Audioscrobbler or MusicStrands.
There are about 700 pages of interesting reading on the ismir 2005 site. If you read 5 papers a week you'll be just about done when ISMIR 2006 rolls around. So get cracking.
For the hard-core math weenies out there, the paper that seems to have the highest density of equations to text is
the paper Harmonic-Temporal Clustering via Deterministic Annealing EM Algorithm for Audio Feature Extraction by Hirokazu Kameoka and friends with 35 labeled equations (one equation consumes nearly half a page of text).
The paper by Charles Parker called Applications of Binary Classification and Adaptive Boosting to the Query-By-Humming Problem is a quite well written paper describing methods of symbolic alignment using binary classifiers. (I tend to favor papers that rely on pseudocode to explain things as opposed to maths, which is Mr. Parker's approach).
Foafing the Music: A Music Recommendation System based on RSS Feeds and User Preferences is a MIR meets Web 2.0 paper with lots of good ideas about combining the various source of music information such as Audioscrobbler or MusicStrands.
There are about 700 pages of interesting reading on the ismir 2005 site. If you read 5 papers a week you'll be just about done when ISMIR 2006 rolls around. So get cracking.