Bob L. T. Sturm 个人学术档案

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引用	3458	2059
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Oded Ben-TalKingston University在 kingston.ac.uk 的电子邮件经过验证
Saumitra MishraExecutive Director at JP Morgan在 jpmorgan.com 的电子邮件经过验证
Emmanouil BenetosQueen Mary University of London, The Alan Turing Institute在 qmul.ac.uk 的电子邮件经过验证
Simon DixonCentre for Digital Music, Queen Mary University of London在 qmul.ac.uk 的电子邮件经过验证
Laurent DaudetProfessor of physics, Paris Cité University / Co-CEO at LightOn在 espci.fr 的电子邮件经过验证
Bhusan ChettriResearcher in AI and Machine Learning for audio and speech在 boracsolutions.com 的电子邮件经过验证
Mads Græsbøll ChristensenProfessor, Dept. of Electronic Systems, Aalborg University在 es.aau.dk 的电子邮件经过验证
Curtis RoadsProfessor of Media Arts and Technology at UCSB在 mat.ucsb.edu 的电子邮件经过验证
Nick Collinsdurham university在 durham.ac.uk 的电子邮件经过验证
Corey KereliukMcGill在 mail.mcgill.ca 的电子邮件经过验证
Andre HolzapfelAssociate Professor, Royal Institute of Technology在 kth.se 的电子邮件经过验证
Jan LarsenTechnical University of Denmark, DTU Compute在 dtu.dk 的电子邮件经过验证
François PachetSpotify Creator Technology Research Lab, director在 spotify.com 的电子邮件经过验证
Daniel StollerSpotify在 spotify.com 的电子邮件经过验证
Iryna KorshunovaGhent University在 ugent.be 的电子邮件经过验证
João Felipe SantosNVIDIA在 nvidia.com 的电子邮件经过验证
Jerry GibsonProfessor of Electrical and Computer Engineering, UCSB在 ece.ucsb.edu 的电子邮件经过验证
Nicolas JonasonPhD Student, KTH Royal Institute of Technology在 kth.se 的电子邮件经过验证
Gaëtan HadjeresResearch Scientist at Sony AI在 sony.com 的电子邮件经过验证
Emmanuel DerutyParis research, Sony Computer Science Laboratories在 sony.com 的电子邮件经过验证

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Bob L. T. Sturm

Associate Professor, KTH Royal Institute of Technology, Stockholm

在 kth.se 的电子邮件经过验证 - 首页

audio and music signal processing music information retrieval music generation evaluation sparse approximation


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Music transcription modelling and composition using deep learning BL Sturm, JF Santos, O Ben-Tal, I Korshunova Proc. 1st Conference on Computer Simulation of Musical Creativity, 2016	216	2016
Local interpretable model agnostic explanations for music content analysis S Mishra, BL Sturm, S Dixon Proc. ISMIR, 2017	178	2017
Deep learning and music adversaries C Kereliuk, BL Sturm, J Larsen IEEE Transactions on Multimedia 17 (11), 2059-2071, 2015	178	2015
Classification accuracy is not enough: On the evaluation of music genre recognition systems BL Sturm Journal of Intelligent Information Systems, 2013	178	2013
A survey of evaluation in music genre recognition BL Sturm Adaptive Multimedia Retrieval: Semantics, Context, and Adaptation 8382, 29-66, 2014	177	2014
A Simple Method to Determine if a Music Information Retrieval System is a “Horse” B Sturm IEEE Trans. Multimedia 16 (6), 1636-1644, 2014	165	2014
An analysis of the GTZAN music genre dataset BL Sturm Proceedings of the second international ACM workshop on Music information …, 2012	165	2012
Comparison of orthogonal matching pursuit implementations BL Sturm, M Christensen Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th …, 2012	161	2012
The GTZAN dataset: Its contents, its faults, their effects on evaluation, and its future use BL Sturm arXiv preprint arXiv:1306.1461, 2013	159	2013
The state of the art ten years after a state of the art: Future research in music information retrieval BL Sturm Journal of new music research 43 (2), 147-172, 2014	127	2014
Machine learning research that matters for music creation: A case study BL Sturm, O Ben-Tal, Ú Monaghan, N Collins, D Herremans, E Chew, ... Journal of New Music Research 48 (1), 36-55, 2019	115	2019
Artificial intelligence and music: open questions of copyright law and engineering praxis BLT Sturm, M Iglesias, O Ben-Tal, M Miron, E Gómez Arts 8 (3), 115, 2019	102	2019
Ensemble models for spoofing detection in automatic speaker verification B Chettri, D Stoller, V Morfi, MAM Ramírez, E Benetos, BL Sturm arXiv preprint arXiv:1904.04589, 2019	96	2019
Ethical dimensions of music information retrieval technology A Holzapfel, B Sturm, M Coeckelbergh Transactions of the International Society for Music Information Retrieval 1 …, 2018	71	2018
Taking the models back to music practice: Evaluating generative transcription models built using deep learning BL Sturm, O Ben-Tal Journal of Creative Music Systems 2, 32-60, 2017	51	2017
Adaptive Concatenative Sound Synthesis and Its Application to Micromontage Compositior BL Sturm Computer Music Journal 30 (4), 46-66, 2006	47	2006
MATConcat: An Application for Exploring Concatenative Sound Synthesis Using MATLAB. BL Sturm ICMC, 2004	45	2004
Musical instrument identification using multiscale mel-frequency cepstral coefficients BL Sturm, M Morvidone, L Daudet Signal Processing Conference (EUSIPCO), 2010 Proceedings of the 18th European, 2010	43	2010
The beyond the fence musical and computer says show documentary S Colton, MT Llano, R Hepworth, J Charnley, CV Gale, A Baron, F Pachet, ... arXiv preprint arXiv:2206.03224, 2022	38	2022
A multimodal system for gesture recognition in interactive music performance D Overholt, J Thompson, L Putnam, B Bell, J Kleban, B Sturm, ... Computer Music Journal 33 (4), 69-82, 2009	38	2009

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