Poster Co-ordinator: Jon Dunn, Indiana University at Bloomington, USA

The following posters are scheduled for presentation at ISMIR2001.(Alpha-ordered by submitting author.)

Submitting author	Poster title
Aucouturier, Jean-Julien Sony CSL Paris, France	Using Long-Term Structure to Retrieve Music: Representation and Matching
Birmingham, William University of Michigan, USA	Statistical Analysis for Music Information Retrieval
Cano, Pedro Music Technology Group, University Pompeu Fabra, Spain	Statistical Significance in Song-Spotting in Audio
Downie, J. Stephen Univesity of Illinois at Urbana-Champaign, USA	The Music Information Retrieval Annotated Bibliograpy Project, Phase I
Fujinaga, Ichiro Johns Hopkins University, USA	Gamera: A structured Document Recognition Application Development Environment
Jang, J.-S. Roger National Tsing Hua University, Taiwan	MIRACLE: A Music Information Retrieval System with Clustered Computing Engines
Lemstrom, Kjell University of Helsinki, Finland	A Three-Layer Approach for Music Retrieval in Large Databases
Mazzoni, Dominic Carnegie Mellon University, USA	Melody Matching Directly From Audio
McPherson, John University of Waikato, New Zealand	Usage of the MELDEX Digital Music Library
Nam, Unjung Stanford University, USA	Addressing the Same but Different - Different but Similar Problem in Automatic Music Classification
Ó Maidín, Donncha University of Limerick, Ireland	Computer-supported Browsing for MIR
Politis, Dionysios Aristotle University of Thessaloniki, Greece	Musical Information Retrieval for Delta and Neumatic Systems
Rolland, Pierre-Yves Atelier de Modelisation et de Prevision, France	Adaptive User Modeling in a Content-Based Music Retrieval System
Smith, Lloyd New Mexico Highlands University, USA	Discovering Themes by Exact Pattern Matching
Sorsa, Timo Nokia Research Center, Finland	Melodic Resolution in Music Retrieval
Spevak, Christian  University of Hertfordshire, UK	Sound Spotting – a Frame-Based Approach
Yang, Cheng  Stanford University, USA	Music Database Retrieval Based on Spectral Similarity