Ramírez, Rafael,1966-Maestre Gómez, EstebanPertusa, AntonioGómez Gutiérrez, Emilia, 1975-Serra, Xavier2018-03-082018-03-082007Ramirez R, Maestre E, Pertusa A, Gómez E, Serra X. Performance-based interpreter identification in saxophone audio recordings. In: IEEE Trans Circuits Syst Video Technol. 2007;17(3):356-64. DOI: 10.1109/TCSVT.2007.8908621558-2205http://hdl.handle.net/10230/34065We propose a novel approach to the task of identifying performers from their playing styles. We investigate how skilled musicians (Jazz saxophone players in particular) express and communicate their view of the musical and emotional content of musical pieces and how to use this information in order to automatically identify performers. We study deviations of parameters such as pitch, timing, amplitude and timbre both at an inter-note level and at an intra-note level. Our approach to performer identification consists of establishing a performer dependent mapping of inter-note features (essentially a "score" whether or not the score physically exists) to a repertoire of inflections characterized by intra-note features. We present a successful performer identification case study.application/pdfeng© 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The final published article can be found at http://ieeexplore.ieee.org/document/4118245/info:eu-repo/semantics/articlehttp://dx.doi.org/10.1109/TCSVT.2007.890862Artificial intelligenceAudio recordingsMusicSignal processinginfo:eu-repo/semantics/openAccess