Dorien Herremans
Cited by
Cited by
A functional taxonomy of music generation systems
D Herremans, CH Chuan, E Chew
ACM Computing Surveys (CSUR) 50 (5), 1-30, 2017
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
Dance Hit Song Prediction
D Herremans, D Martens, K Sörensen
Journal of New Music Research, Special Issue on Music and Machine Learning …, 2014
MorpheuS: generating structured music with constrained patterns and tension
D Herremans, E Chew
IEEE Transactions on Affective Computing 10 (4), 510-523, 2017
nnAudio: An on-the-fly gpu audio to spectrogram conversion toolbox using 1d convolutional neural networks
KW Cheuk, H Anderson, K Agres, D Herremans
IEEE Access 8, 161981-162003, 2020
Hear: Holistic evaluation of audio representations
J Turian, J Shier, HR Khan, B Raj, BW Schuller, CJ Steinmetz, C Malloy, ...
NeurIPS 2021 Competitions and Demonstrations Track, 125-145, 2022
Toward robust audio spoofing detection: A detailed comparison of traditional and learned features
BT Balamurali, KE Lin, S Lui, JM Chen, D Herremans
IEEE Access 7, 84229-84241, 2019
Tension ribbons: Quantifying and visualising tonal tension.
D Herremans, E Chew
Second International Conference on Technologies for Music Notation and …, 2016
Music, computing, and health: a roadmap for the current and future roles of music technology for health care and well-being
KR Agres, RS Schaefer, A Volk, S Van Hooren, A Holzapfel, S Dalla Bella, ...
Music & Science 4, 2059204321997709, 2021
Music fadernets: Controllable music generation based on high-level features via low-level feature modelling
HH Tan, D Herremans
International Society of Music Information Retrieval (ISMIR), 2020
Generating structured music for bagana using quality metrics based on Markov models
D Herremans, S Weisser, K Sörensen, D Conklin
Expert Systems with Applications 42 (21), 7424–7435, 2015
Composing Fifth Species Counterpoint Music With A Variable Neighborhood Search Algorithm
D Herremans, K Sörensen
Expert Systems with Applications 40 (16), 6427--6437, 2013
Modeling Musical Context with Word2vec
D Herremans, CH Chuan
First International Workshop on Deep Learning and Music, Anchorage, US 1 (1 …, 2017
Composing first species counterpoint with a variable neighbourhood search algorithm
D Herremans, K Sörensen
Journal of Mathematics and the Arts 6 (4), 169-189, 2012
From context to concept: exploring semantic relationships in music with word2vec
CH Chuan, K Agres, D Herremans
Neural Computing and Applications 32, 1023-1036, 2020
Learning disentangled representations of timbre and pitch for musical instrument sounds using gaussian mixture variational autoencoders
YJ Luo, K Agres, D Herremans
20th Conference of the International Society for Music Information Retrieval …, 2019
Singing voice conversion with disentangled representations of singer and vocal technique using variational autoencoders
YJ Luo, CC Hsu, K Agres, D Herremans
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
Modeling Temporal Tonal Relations in Polyphonic Music Through Deep Networks with a Novel Image-Based Representation
CH Chuan, D Herremans
AAAI, 2018
Singing voice separation using a deep convolutional neural network trained by ideal binary mask and cross entropy
KWE Lin, BT Balamurali, E Koh, S Lui, D Herremans
Neural Computing and Applications 32, 1037-1050, 2020
Development of machine learning for asthmatic and healthy voluntary cough sounds: a proof of concept study
HI Hee, BT Balamurali, A Karunakaran, D Herremans, OH Teoh, KP Lee, ...
Applied Sciences 9 (14), 2833, 2019
The system can't perform the operation now. Try again later.
Articles 1–20