Παρακολούθηση
Bob L. T. Sturm
Bob L. T. Sturm
Associate Professor, KTH Royal Institute of Technology, Stockholm
Η διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα kth.se - Αρχική σελίδα
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Παρατίθεται από
Παρατίθεται από
Έτος
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
2532016
Local interpretable model agnostic explanations for music content analysis
S Mishra, BL Sturm, S Dixon
Proc. ISMIR, 2017
2382017
Deep learning and music adversaries
C Kereliuk, BL Sturm, J Larsen
IEEE Transactions on Multimedia 17 (11), 2059-2071, 2015
1882015
Classification accuracy is not enough: On the evaluation of music genre recognition systems
BL Sturm
Journal of Intelligent Information Systems, 2013
1862013
A survey of evaluation in music genre recognition
BL Sturm
Adaptive Multimedia Retrieval: Semantics, Context, and Adaptation 8382, 29-66, 2014
1822014
A Simple Method to Determine if a Music Information Retrieval System is a “Horse”
B Sturm
IEEE Trans. Multimedia 16 (6), 1636-1644, 2014
1792014
The GTZAN dataset: Its contents, its faults, their effects on evaluation, and its future use
BL Sturm
arXiv preprint arXiv:1306.1461, 2013
1772013
An analysis of the GTZAN music genre dataset
BL Sturm
Proceedings of the second international ACM workshop on Music information …, 2012
1712012
Comparison of orthogonal matching pursuit implementations
BL Sturm, M Christensen
Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th …, 2012
1692012
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
1382019
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
1352019
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
1332014
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
1042019
Ethical dimensions of music information retrieval technology
A Holzapfel, B Sturm, M Coeckelbergh
Transactions of the International Society for Music Information Retrieval 1 …, 2018
902018
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
562017
Adaptive Concatenative Sound Synthesis and Its Application to Micromontage Composition
BL Sturm
Computer Music Journal 30 (4), 46-66, 2006
512006
MATConcat: An Application for Exploring Concatenative Sound Synthesis Using MATLAB.
BL Sturm
ICMC, 2004
472004
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
442010
Analysing the predictions of a cnn-based replay spoofing detection system
B Chettri, S Mishra, BL Sturm, E Benetos
2018 IEEE spoken language technology workshop (SLT), 92-97, 2018
412018
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
402022
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