Zobrazeno 1 - 10
of 43
pro vyhledávání: '"Hazan, Amaury"'
Autor:
Hazan, Amaury
Publikováno v:
TDX (Tesis Doctorals en Xarxa).
We develop in this thesis a computational model of music expectation, which may be one of the most important aspects in music listening. Many phenomenons related to music listening such as preference, surprise or emo- tions are linked to the anticipa
Externí odkaz:
http://hdl.handle.net/10803/22721
Akademický článek
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Publikováno v:
Computer Music Journal, 2008 Apr 01. 32(1), 38-50.
Externí odkaz:
https://www.jstor.org/stable/40072663
Autor:
Purwins, Hendrik, Grachten, Maarten, Herrera, Perfecto, Hazan, Amaury, Marxer, Ricard, Serra, Xavier
Publikováno v:
In Physics of Life Reviews 2008 5(3):169-182
Autor:
Purwins, Hendrik, Herrera, Perfecto, Grachten, Maarten, Hazan, Amaury, Marxer, Ricard, Serra, Xavier
Publikováno v:
In Physics of Life Reviews 2008 5(3):151-168
Autor:
Hazan, Amaury1 (AUTHOR) amaury.hazan@upf.edu, Marxer, Ricard1 (AUTHOR), Brossier, Paul1 (AUTHOR), Purwins, Hendrik1 (AUTHOR), Herrera, Perfecto1 (AUTHOR), Serra, Xavier1 (AUTHOR)
Publikováno v:
Connection Science. Jun2009, Vol. 21 Issue 2/3, p119-143. 25p. 2 Diagrams, 5 Charts, 7 Graphs.
Autor:
Ramirez, Rafael1 (AUTHOR) rafael@iua.upf.es, Hazan, Amaury1 (AUTHOR), Gómez, Emilia1 (AUTHOR), Maestre, Esteban1 (AUTHOR), Serra, Xavier1 (AUTHOR)
Publikováno v:
Journal of New Music Research. Dec2005, Vol. 34 Issue 4, p319-330. 12p. 7 Diagrams, 1 Graph.
Autor:
Hazan, Amaury
We present a doctoral pre-thesis report focusing of inductive computational modeling of music performance. We first introduce the expressive performance phenomenon from various points of view musicology, music cognition, computer music and brain scie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::20ee1762f79a29ee782ed861dc93a0bf
Publikováno v:
Journées d'informatique musicale
Journées d'informatique musicale, 2004, Paris, France
Journées d'informatique musicale, 2004, Paris, France
International audience; In this paper, we describe an approach to learning expressive performance rules from monophonic Jazz standards recordings by a skilled saxophonist. We have first developed a melodic transcription system which extracts a set of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1221cd4d8a06f211910b141728496419
https://hal.archives-ouvertes.fr/hal-03354365/file/P42.pdf
https://hal.archives-ouvertes.fr/hal-03354365/file/P42.pdf
Autor:
RAMIREZ, RAFAEL1 rafael@iua.upf.es, HAZAN, AMAURY1 ahazan@iua.upf.es
Publikováno v:
International Journal on Artificial Intelligence Tools. Aug2006, Vol. 15 Issue 4, p673-691. 19p. 4 Illustrations, 1 Diagram, 3 Charts, 2 Graphs.