Rebecca Fiebrink

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Ge WangAssociate Professor of Music (also Computer Science), Stanford UniversityVerified email at ccrma.stanford.edu
Marco GilliesProfessor in Computing, Goldsmiths, University of LondonVerified email at gold.ac.uk
Spencer SalazarPrincipal Engineer, Output Inc.Verified email at ccrma.stanford.edu
Michael ZbyszyńskiVerified email at mikezed.com
Baptiste CaramiauxCNRS researcher (HDR), ISIR, Sorbonne UniversitéVerified email at lri.fr
Ichiro FujinagaProfessor, Music Technology Area, Schulich School of Music, McGill UniversityVerified email at mcgill.ca
Marcelo M. WanderleyProfessor, Music Technology - McGill UniversityVerified email at mcgill.ca
Joseph MallochAssistant Professor, Dalhousie UniversityVerified email at dal.ca
Memo AktenGoldsmiths, University of LondonVerified email at msavisuals.com
Reid OdaPrinceton UniversityVerified email at princeton.edu
Francisco BernardoPostdoctoral Research Fellow, University College LondonVerified email at ucl.ac.uk
Annie KellyUniversity of Colorado BoulderVerified email at colorado.edu
Atau TanakaGoldsmiths, University of LondonVerified email at goldsmithsdigital.com
Cory McKayProfessor of Music, Marianopolis CollegeVerified email at mail.mcgill.ca
Dan MorrisResearch Scientist, Google AI for Nature and SocietyVerified email at cs.stanford.edu
Hugo Scurtoartist, designer & researcher (PhD)Verified email at hugoscurto.com
Meredith Ringel MorrisDirector, Human-AI Interaction Research, Google DeepMindVerified email at google.com
margaret schedelStony Brook UniversityVerified email at stonybrook.edu
Zafer BarutcuogluPh.D. in Computer Science, Princeton UniversityVerified email at cs.princeton.edu
Christopher DeCoroPh.D. in Computer Science, Princeton UniversityVerified email at cs.princeton.edu

Rebecca Fiebrink

Professor, Creative Computing Institute, University of the Arts London

Verified email at arts.ac.uk - Homepage

Human-computer interaction machine learning technologies for music and creative expression


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Human model evaluation in interactive supervised learning R Fiebrink, PR Cook, D Trueman Proceedings of the SIGCHI conference on human factors in computing systems …, 2011	203	2011
A meta-instrument for interactive, on-the-fly machine learning R Fiebrink, D Trueman, PR Cook International Conference on New Interfaces for Musical Expression (NIME), 2009	169	2009
Real-time human interaction with supervised learning algorithms for music composition and performance RA Fiebrink Princeton University, 2011	160	2011
Human-centred machine learning M Gillies, R Fiebrink, A Tanaka, J Garcia, F Bevilacqua, A Heloir, ... Proceedings of the 2016 CHI conference extended abstracts on human factors …, 2016	159	2016
Towards a dimension space for musical devices D Birnbaum, R Fiebrink, J Malloch, MM Wanderley NIME 5, 192-195, 2005	142	2005
The Wekinator: a system for real-time, interactive machine learning in music R Fiebrink, PR Cook Proceedings of The Eleventh International Society for Music Information …, 2010	122	2010
Don't forget the laptop: using native input capabilities for expressive musical control R Fiebrink, G Wang, PR Cook Proceedings of the 7th international conference on New interfaces for …, 2007	85	2007
Machine learning education for artists, musicians, and other creative practitioners R Fiebrink ACM Transactions on Computing Education (TOCE) 19 (4), 1-32, 2019	80	2019
Mixed-initiative creative interfaces S Deterding, J Hook, R Fiebrink, M Gillies, J Gow, M Akten, G Smith, ... Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors …, 2017	80	2017
Continuous score-coded pitch correction S Salazar, RA Fiebrink, G Wang, M Ljungström, JC Smith, PR Cook US Patent 9,147,385, 2015	76	2015
Bayesian Aggregation for Hierarchical Genre Classification. C DeCoro, Z Barutcuoglu, R Fiebrink ISMIR, 77-80, 2007	73	2007
From rituals to magic: Interactive art and HCI of the past, present, and future M Jeon, R Fiebrink, EA Edmonds, D Herath International Journal of Human-Computer Studies 131, 108-119, 2019	65	2019
ACE: A Framework for Optimizing Music Classification. C McKay, R Fiebrink, D McEnnis, B Li, I Fujinaga ISMIR, 42-49, 2005	65	2005
Toward understanding human-computer interaction in composing the instrument R Fiebrink, D Trueman, NC Britt, M Nagai, K Kaczmarek, M Early, ... ICMC, 2010	60	2010
The machine learning algorithm as creative musical tool R Fiebrink, B Caramiaux arXiv preprint arXiv:1611.00379, 2016	59	2016
Using interactive machine learning to support interface development through workshops with disabled people S Katan, M Grierson, R Fiebrink Proceedings of the 33rd annual ACM conference on human factors in computing …, 2015	57	2015
How machine learning impacts the undergraduate computing curriculum RB Shapiro, R Fiebrink, P Norvig Communications of the ACM 61 (11), 27-29, 2018	56	2018
World stage for pitch-corrected vocal performances S Salazar, RA Fiebrink, G Wang, M Ljungström, JC Smith, J Yang US Patent 8,682,653, 2014	55	2014
Feature Selection Pitfalls and Music Classification. R Fiebrink, I Fujinaga ISMIR, 340-341, 2006	54	2006
Dynamic mapping of physical controls for tabletop groupware R Fiebrink, D Morris, MR Morris Proceedings of the SIGCHI Conference on Human Factors in Computing Systems …, 2009	49	2009

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