Technical Program

AASP-L3: Signal Processing for Music

Session Type: Lecture
Time: Wednesday, March 23, 16:00 - 18:00
Location: Room 3C+3D
Session Chairs: Sascha Spors, University of Rostock and Antoine Liutkus, INRIA
 
AASP-L3.1: A SCORE-INFORMED SHIFT-INVARIANT EXTENSION OF COMPLEX MATRIX FACTORIZATION FOR IMPROVING THE SEPARATION OF OVERLAPPED PARTIALS IN MUSIC RECORDINGS
         Francisco J. Rodriguez-Serrano; Universidad de Jaen
         Sebastian Ewert; Queen Mary University of London
         Pedro Vera-Candeas; Universidad de Jaen
         Mark Sandler; Queen Mary University of London
 
AASP-L3.2: PHRASE-BASED RĀGA RECOGNITION USING VECTOR SPACE MODELING
         Sankalp Gulati; Universitat Pompeu Fabra
         Joan Serrà; Telefonica Research
         Vignesh Ishwar; Universitat Pompeu Fabra
         Sertan Şentürk; Universitat Pompeu Fabra
         Xavier Serra; Universitat Pompeu Fabra
 
AASP-L3.3: MUSIC EMOTION RECOGNITION WITH ADAPTIVE AGGREGATION OF GAUSSIAN PROCESS REGRESSORS
         Satoru Fukayama; National Institute of Advanced Industrial Science and Technology
         Masataka Goto; National Institute of Advanced Industrial Science and Technology
 
AASP-L3.4: A GENERALIZED BAYESIAN MODEL FOR TRACKING LONG METRICAL CYCLES IN ACOUSTIC MUSIC SIGNALS
         Ajay Srinivasamurthy; Universitat Pompeu Fabra
         Andre Holzapfel; Austrian Research Institute for Artificial Intelligence
         Ali Taylan Cemgil; Boğaziçi University
         Xavier Serra; Universitat Pompeu Fabra
 
AASP-L3.5: OPTIMIZING DTW-BASED AUDIO-TO-MIDI ALIGNMENT AND MATCHING
         Colin Raffel; Columbia University
         Daniel P. W. Ellis; Columbia University
 
AASP-L3.6: FAST AND STATISTICALLY EFFICIENT FUNDAMENTAL FREQUENCY ESTIMATION
         Jesper Kjær Nielsen; Aalborg University and Bang & Olufsen
         Tobias Lindstrøm Jensen; Aalborg University
         Jesper Rindom Jensen; Aalborg University
         Mads Græsbøll Christensen; Aalborg University
         Søren Holdt Jensen; Aalborg University
 

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