Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Amaury Hazan"'
Autor:
Iordanis Thoidis, Amaury Hazan, Ad Snik, Jonatan Rivilla, Kamil Budzyński, Num Mendez, Jacques Kinsbergen
Publikováno v:
Frontiers in Audiology and Otology, Vol 2 (2024)
BackgroundHome-based remote audiometry has been emerging due to the increasing accessibility of mobile technology and the need for healthcare solutions that are available worldwide. However, the challenges presented by uncontrolled conditions, such a
Externí odkaz:
https://doaj.org/article/b76c59d77bc64f14abb90258e961f3be
Autor:
Amaury, Hazan, Joanna, Luberadzka, Jonatan, Rivilla, Ad, Snik, Bert, Albers, Num, Méndez, Nicolas, Wack, Oscar, Paytuvi, Andrzej, Zarowski, Erwin, Offeciers, Jacques, Kinsbergen
Publikováno v:
American Journal of Audiology. 31:914-922
Purpose: The aim of this study was to assess the test–retest reliability of a smartphone-based hearing test, performed without supervision of a hearing professional in an uncontrolled environment. Method: The hearing application is based on an auto
Publikováno v:
Recercat. Dipósit de la Recerca de Catalunya
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A causal system to represent a stream of music into musical events, and to generate further expected events, is presented. Starting from an auditory front-end that extracts low-level (i.e. MFCC) and mid-level features such as onsets and beats, an uns
Autor:
Hendrik Purwins, Maarten Grachten, Amaury Hazan, Xavier Serra, Ricard Marxer, Perfecto Herrera
Publikováno v:
Recercat. Dipósit de la Recerca de Catalunya
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In Part I [Purwins H, Herrera P, Grachten M, Hazan A, Marxer R, Serra X. Computational models of music perception and cognition I: The perceptual and cognitive processing chain. Physics of Life Reviews 2008, in press, doi:10.1016/j.plrev.2008.03.004]
Publikováno v:
Computer Music Journal. 32:38-50
Autor:
Amaury Hazan, Rafael Ramirez
Publikováno v:
International Journal on Artificial Intelligence Tools. 15:673-691
In this paper we present a machine learning approach to modeling the knowledge applied by a musician when performing a score in order to produce an expressive performance of a piece. We describe a tool for both generating and explaining expressive mu
Autor:
Hazana, Amaury1 amaury@jacoti.com, Luberadzka, Joanna1,2, Rivilla, Jonatan1, Snik, Ad1,3, Albers, Bert1,4, Méndez, Num1, Wack, Nicolas1, Paytuvi, Oscar1, Zarowski, Andrzej1,5, Offeciers, Erwin1, Kinsbergen, Jacques1
Publikováno v:
American Journal of Audiology. 2022 Supplement, Vol. 31, p914-922. 9p. 1 Diagram, 4 Charts, 1 Graph.
Autor:
Henkjan Honing, Leigh M. Smith, Piotr Holonowicz, Susan L. Denham, Martin Coath, Amaury Hazan, Hendrik Purwins
Publikováno v:
Connection Science, 21(2-3), 193-205. Taylor and Francis AS
We describe a biophysically motivated model of auditory salience based on a model of cortical responses and present results that show that the derived measure of salience can be used to identify the position of perceptual onsets in a musical stimulus
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4defeb1dc82e3f64f7df228200eaea1
https://dare.uva.nl/personal/pure/en/publications/model-cortical-responses-for-the-detection-of-perceptual-onsets-and-beat-tracking-in-singing(5f20715f-7a74-4842-8bff-12fa3594f971).html
https://dare.uva.nl/personal/pure/en/publications/model-cortical-responses-for-the-detection-of-perceptual-onsets-and-beat-tracking-in-singing(5f20715f-7a74-4842-8bff-12fa3594f971).html
Publikováno v:
Natural Computing Series ISBN: 9783540728764
The Art of Artificial Evolution
The Art of Artificial Evolution
We describe an evolutionary approach to one of the most challenging problems in computer music: modeling the knowledge applied by a musician when performing a score of a piece in order to produce an expressive performance of the piece. We extract a s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5acfaa1a1d7a6bd4f845708f0f351ea4
https://doi.org/10.1007/978-3-540-72877-1_6
https://doi.org/10.1007/978-3-540-72877-1_6
Publikováno v:
Multimedia Data Mining and Knowledge Discovery ISBN: 9781846284366
In this chapter we present a data mining approach to one of the most challenging aspects of computer music: modeling the knowledge applied by a musician when performing a score in order to produce an expressive performance of a piece. We apply data m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b48b456ca7d3f231e9a3e67bf0c09ac
https://doi.org/10.1007/978-1-84628-799-2_18
https://doi.org/10.1007/978-1-84628-799-2_18