International Symposium on Music Information Retrieval
Technical Program
and Links to Symposium Documents (PDF)
Keynote Speaker
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Marvin Minsky
MIT Media Lab
How We Recognize Music: The Musical Society of Mind
Invited Speakers
Coordinated by Don Byrd, CIIR, University of Massachusetts
Accepted Papers
Coordinated by J. Stephen Downie, Graduate School of Library and Information
Science, University of Illinois
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Techniques for Automatic Music Transcription
Juan Pablo Bello, Giuliano Monti, and Mark Sandler
Department of Electronic Engineering, King's College London
Extended
Abstract
Full-text
Paper
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Optical Music Recognition System within a Large-Scale Digitization Project
G.S. Choudhury, M. Droetboom, T. DiLauro, I. Fujinaga, and B. Harrington
Eisenhower Library and Peabody Institute, Johns Hopkins University
Extended
Abstract Full-text
Paper
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PROMS: A Web-based Tool for Searching in Polyphonic Music
M. Clausen, R. Engelbrecht, D. Meyer, and J. Schmitz
Institut fuer Informatik V, Universitaet Bonn, Germany
Extended
Abstract
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ARTHUR: Retrieving Orchestral Music by Long-Term Structure
Jonathan Foote
FX Palo Alto Laboratory
Extended
Abstract Full-text
Paper
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Towards Instrument Segmentation for Music Content Description:
a Critical Review of Instrument Classification Techniques
Perfecto Herrera-Boyer, Xavier Amatriain, Eloi Batlle, and Xavier Serra
Audiovisual Institute - Pompeu Fabra University, Barcelona, Spain
Extended
Abstract Full-text
Paper
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SEMEX - An efficient Music Retrieval Prototype
K. Lemstrom and S. Perttu
Dept. of Computer Science, University of Helsinki
Extended
Abstract Full-text
Paper
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Mel Frequency Cepstral Coefficients for Music Modeling
Beth Logan
Compaq, Cambridge, MA
Extended
Abstract Full-text
Paper
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A Comparison of Language Modeling and Probabilistic Text Information
Retrieval
Approaches to Monophonic Music Retrieval
Jeremy Pickens
CIIR, Dept. of Computer Science, University of Massachusetts/Amherst
Extended
Abstract Full-text
Paper
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XML4MIR: Extensible Markup Language for Music Information Retrieval
Perry Roland
Digital Library Research Group, University of Virginia
Extended
Abstract Full-text
Paper
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Audio Information Retrieval (AIR) Tools
George Tzanetakis and Perry Cook
Dept. of Computer Science and Dept. of Music, Princeton University
Extended
Abstract Full-text
Paper
Posters
Coordinated by Craig Nevill-Manning, Computer Science Department, Rutgers University
- Automatic Segmentation for Music Classification using Competitive Hidden Markov Models
Elio Batlle and Pedro Cano, Universitat Pompeu Fabra
- Time Domain Extraction of Vibrato from Monophonic Instruments
Daniel Bendor, University of Maryland at College Park,
and Mark Sandler, King's College, London
- MuTaTeD'll: A System for Music Information Retrieval of Encoded Music
Donald MacLellan and Carola Boehm, University of Glasgow
- Using User Models in Music Information Retrieval Systems
Wei Chai and Barry Vercoe, Massachusetts Institute of Technology
- Exploration of Point-Distribution Models for Similarity-based Classification and Indexing of Polyphonic Music
Dave Cliff and Heppie Freeburn, Hewlett-Packard Labs
- Finding Motifs with Gaps
Maxime Crochemore, Universite de Marne-la-Vallee,
Costas S. Iliopoulos and Yoan J. Pinzon, Curtin University of Technology,
and Wojciech Rytter, Uniwersytet Warszawski and University of Liverpool
- A Music Interface for Visually Impaired People in the WEDELMUSIC Environment. Design and Architecture
Anastasia Georgaki, Spyros Raptis, and Stelios Bakamidis, Institute for Language and Speech Processing
- Representing Music Using XML
Michael Good, Recordare
- Subject Search for Music: Quantitative Analysis of Access Point Selection
Mari Itoh, Aichi Shukutoku University
- Using a Spectral Flatness Based Feature for Audio Segmentation and Retrieval
Ozgur Izmirli, Connecticut College
- Score-based Style Recognition Using Artificial Neural Networks
Francis J. Kiernan, University of Jyvaskyla, Finland
- Analysis of a Contour-based Representation for Melody
Youngmoo E. Kim, Wei Chai, Ricardo Garcia, and Barry Vercoe, Massachusetts Institute of Technology Media Lab
- Integrating Paper and Digital Music Information Systems
Karen Lin and Tim Bell, University of Canterbury
Full-text
Paper
- MCML - Music Contents Markup Language
Jochen Schimmelpfennig and Frank Kurth, University of Bonn
- Music Ranking Techniques Evaluated
Alexandra L. Uitdenbogerd, Justin Zobel, RMIT University
- From Raw Polyphonic Audio to Locating Recurring Themes
Thomas von Schroeter, Imperial College of Science Technology and Medicine,
Shyamala Doraisamy, University Putra Malaysia,
and Stefan M. Ruger, Imperial College of Science Technology and Medicine
Full-text
Paper
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