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BT B, Aslim E.J, Ng YShu Lynn, Kuo TLi Chuen, Chen JShihang, Herremans D., Ng LGuat, Chen J.M..  2020.  Acoustic prediction of flowrate: varying liquid jet stream onto a free surface. IEEE International Conference on Signal Processing and Communications (SPCOM). PDF icon preprint flow.pdf (1.01 MB)
Nahar F., Agres K., BT B, Herremans D..  2020.  A dataset and classification model for Malay, Hindi, Tamil and Chinese music. 13th Workshop on music and machine learning (MML) as part of ECML/PKDD.
Tan HHao, Luo Y.J., Herremans D..  2020.  Generative Modelling for Controllable Audio Synthesis of Expressive Piano Performance. Workshop on Machine Learning for Music Discover (ML4MD) as part of ICML. PDF icon 2006.09833.pdf (2.81 MB)
Cheuk K.W., Agres K., Herremans D..  2020.  The impact of Audio input representations on neural network based music transcription. Proceedings of the International Joint Conference on Neural Networks (IJCNN). PDF icon 2001.09989.pdf (1.87 MB)
Tan H.H., Herremans D..  2020.  Music FaderNets: Controllable Music Generation Based On High-Level Features via Low-Level Feature Modelling. ISMIR.
Cheuk K.W., Anderson H., Agres K., Herremans D..  2020.  nnAudio: An on-the-fly GPU Audio to Spectrogram Conversion Toolbox Using 1D Convolution Neural Networks. IEEE Access.
Garg K., Singh A., Herremans D., Lall B..  2020.  PerceptionGAN: Real-world image construction from provided text through perceptual understanding. 4th Int. Conf. on Imaging, Vision and Pattern Recognition (IVPR), and 9th Int. Conf. on Informatics, Electronics & Vision (ICIEV). PDF icon perceptionGAN-preprint.pdf (2.83 MB)
Cheuk K.W., Luo Y.J., BT B, Roig G., Herremans D..  2020.  Regression-based music emotion prediction using triplet neural networks. Proceedings of the International Joint Conference on Neural Networks (IJCNN). PDF icon 2001.09988.pdf (777.31 KB)
Luo Y.J., Hsu C.-C., Agres K., Herremans D..  2020.  Singing voice conversion with disentangled representations of singer and vocal technique using variational autoencoders. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP). PDF icon 1912.02613.pdf (2.9 MB)
Hee H.I., BT B, Karunakaran A., Herremans D., Teoh O.H., Lee K.P., Teng S.S., Lui S., Chen J.M..  2019.  Development of Machine Learning for asthmatic and healthy voluntary cough - a proof of concept study. Applied Sciences. 9(14)PDF icon applsci-09-02833.pdf (2.06 MB)
Lee-Leon A., Yuen C., Herremans D..  2019.  Doppler Invariant Demodulation for Shallow Water Acoustic Communications Using Deep Belief Networks. 16th IEEE Asia Pacific Wireless Communications Symposium (APWCS). PDF icon 1909.02850.pdf (790.54 KB)
Herremans D., Chuan C.-H..  2019.  The emergence of deep learning: new opportunities for music and audio technologies. Neural Computing and Applications. PDF icon main_preprint.pdf (102.16 KB)
Lee-Leon A., Yuen C., Herremans D..  2019.  A Hybrid Fuzzy Logic-Neural Network Approach For Multi-path Separation Of Underwater Acoustic Signals. 89th IEEE Vehicular Technology Conference. PDF icon fuzzy logic.pdf (1.66 MB)
Agres K., Bigo L., Herremans D..  2019.  The impact of musical structure on enjoyment and absorptive listening states in trance music. Music and Consciousness 2 - Worlds, Practices, Modalities.
Cheuk K.W., BT B, Roig G., Herremans D..  2019.  Latent space representation for multi-target speaker detection and identification with a sparse dataset using Triplet neural networks. IEEE Automatic Speech Recognition and Understanding Workshop (ASRU 2019). PDF icon 1910.01463.pdf (934.76 KB)
Luo Y.J., Agres K., Herremans D..  2019.  Learning Disentangled Representations of Timbre and Pitch for Musical Instrument Sounds Using Gaussian Mixture Variational Autoencoders. ISMIR. PDF icon jyun-ismir.pdf (5.62 MB)
Sturm B., Ben-Tal O., Monaghan U., Collins N., Herremans D., Chew E., Hadjeres G., Deruty E., Pachet F..  2019.  Machine Learning Research that Matters for Music Creation: A Case Study. Journal of New Music Research. 48(1):36-55.PDF icon concert_paper_preprint.pdf (1.6 MB)
T. Phuong HThi, Herremans D., Roig G..  2019.  Multimodal Deep Models for Predicting Affective Responses Evoked by Movies. The 2nd International Workshop on Computer Vision for Physiological Measurement as part of ICCV. Seoul, South Korea. 2019. PDF icon 1909.06957.pdf (836.3 KB)
Cheuk K.W., Agres K., Herremans D..  2019.  nnAudio: A PyTorch Audio Processing Tool Using 1D Convolution neural networks. ISMIR - Late Breaking Demo. PDF icon nnAudio.pdf (399.08 KB)
Agres K., Lui S., Herremans D..  2019.  A novel music-based game with motion capture to support cognitive and motor function in the elderly. IEEE Conference on Games. PDF icon preprint.pdf (2.6 MB)
Herremans D., Chew E..  2019.  Towards emotion based music generation: A tonal tension model based on the spiral array. Proceedings of Cognitive Science (CogSci). PDF icon CogSci_tension (1).pdf (610.91 KB)
BT B, Lin K.W.E., Lui S., Chen J.M., Herremans D..  2019.  Towards robust audio spoofing detection: a detailed comparison of traditional and learned features. IEEE Access. 7:84229-84241.PDF icon ieee_access_herremans.pdf (14.31 MB)
Cheuk K.W., BT B, Roig G., Herremans D..  2018.  Blacklisted speaker identification using triplet neural networks. MCE2018 competition. PDF icon SUTD_description.pdf (133.08 KB)
Chuan C.-H., Agres K., Herremans D..  2018.  From Context to Concept: Exploring Semantic Relationships in Music with Word2Vec. Neural Computing and Applications. PDF icon paper.pdf (1.64 MB)
Agus N., Anderson H., Chen J.M., Lui S., Herremans D..  2018.  Minimally Simple Binaural Room Modelling Using a Single Feedback Delay Network. Journal of the Audio Engineering Society. 66(10):791-807.PDF icon angus_jaes_preprint.pdf (6.39 MB)
Chuan C.-H., Herremans D..  2018.  Modeling temporal tonal relations in polyphonic music through deep networks with a novel image-based representation. The Thirty-Second AAAI Conference on Artificial Intelligence. PDF icon preprint_lstm.pdf (741.28 KB)
Sokolovskis J., Herremans D., Chew E..  2018.  A Novel Interface for the Graphical Analysis of Music Practice Behaviours. Frontiers in Psychology - Human-Media Interaction. 9PDF icon practice_browser.pdf (4.9 MB)
Herremans D., Chew E..  2018.  O.R. and music generation. OR/MS Today. 45(1)PDF icon O.R. and music generation - INFORMS.pdf (825.66 KB)
Agus N., Anderson H., Chen J.M., Lui S., Herremans D..  2018.  Perceptual evaluation of measures of spectral variance. Journal of the Acoustical Society of America. 143(6):3300–3311.PDF icon jasa_an_dh_preprint.pdf (2.46 MB)
Lin K.W.E., BT B, Koh E., Lui S., Herremans D..  2018.  Singing Voice Separation Using a Deep Convolutional Neural Network Trained by Ideal Binary Mask and Cross Entropy. Neural Computing and Applications. PDF icon main.pdf (2.59 MB)
Agres K., Herremans D..  2018.  The Structure of Chord Progressions Influences Listeners’ Enjoyment and Absorptive States in EDM. 15th International Conference on Music Perception and Cognition. PDF icon Agres460_preprint_v2.pdf (387.15 KB)
Herremans D., Chuan C.-H., Chew E..  2017.  A Functional Taxonomy of Music Generation Systems. ACM Computing Surveys. 50(5):30.PDF icon music_generation_survey_dh_preprint.pdf (349.15 KB)
Agres K., Herremans D., Bigo L., Conklin D..  2017.  Harmonic Structure Predicts the Enjoyment of Uplifting Trance Music. Frontiers in Psychology, Cognitive Science. 7(1999)PDF icon agres16ut.pdf (1.15 MB)
Herremans D., Bergmans T..  2017.  Hit Song Prediction Based on Early Adopter Data and Audio Features. The 18th International Society for Music Information Retrieval Conference (ISMIR) - Late Breaking Demo. PDF icon paper_preprint_hit.pdf (221.73 KB)
Herremans D., Yang S., Chuan C.-H., Barthet M., Chew E..  2017.  IMMA-Emo: A Multimodal Interface for Visualising Score- and Audio-synchronised Emotion Annotations. Audio Mostly. PDF icon IMMA-emo_preprint.pdf (1.4 MB)
Herremans D., Chuan C.-H..  2017.  Modeling Musical Context with Word2vec. First International Workshop On Deep Learning and Music. 1:11-18.PDF icon herremans2017work2vec.pdf (745.8 KB)
Herremans D., Chew E..  2017.  MorpheuS: generating structured music with constrained patterns and tension. IEEE Transactions on Affective Computing. PP (In Press)(99)PDF icon herremans2017morpheusFullIEEE.pdf (5.71 MB)
Herremans D., Chuan C.-H..  2017.  A multi-modal platform for semantic music analysis: visualizing audio- and score-based tension. 11th International Conference on Semantic Computing IEEE ICSC 2017. PDF icon paper_preprint.pdf (1.63 MB)
Agres K., Herremans D..  2017.  Music and Motion-Detection: A Game Prototype for Rehabilitation and Strengthening in the Elderly. IEEE International Conference on Orange Technologies (ICOT) . PDF icon agres_herr_music_rehab_preprint.pdf (1.77 MB)
Balliauw M., Herremans D., D. Cuervo P, Sörensen K..  2017.  A variable neighborhood search algorithm to generate piano fingerings for polyphonic sheet music. International Transactions in Operational Research, Special Issue on Variable Neighbourhood Search. 24(3):509–535.PDF icon ITOR_VNS_APF_preprint.pdf (840.28 KB)
Herremans D., Lauwers W..  2017.  Visualizing the evolution of alternative hit charts. The 18th International Society for Music Information Retrieval Conference (ISMIR) - Late Breaking Demo. PDF icon dh_visualiation_preprint.pdf (5.34 MB)
Agres K., Bigo L., Herremans D., Conklin D..  2016.  The Effect of Repetitive Structure on Enjoyment in Uplifting Trance Music. 14th International Conference for Music Perception and Cognition (ICMPC). :280-282.PDF icon preprint_trance.pdf (139.27 KB)
Herremans D., Chew E..  2016.  MorpheuS: Automatic music generation with recurrent pattern constraints and tension profiles. IEEE TENCON. PDF icon paper_morpheus_dh_ieee.pdf (550.61 KB)
Herremans D., Chew E..  2016.  MorpheuS: constraining structure in automatic music generation. Dagstuhl seminar on Computational Music Structure Analysis. PDF icon abstract_dagstuhl_dh.pdf (88.49 KB)
Herremans D., Chew E..  2016.  Music generation with structural constraints: an operations research approach. 30th Annual Conference of the Belgian Operational Research (OR) Society (ORBEL30). :37-39.PDF icon orbel30_dh.pdf (117.78 KB)
Herremans D., Chew E..  2016.  Tension ribbons: Quantifying and visualising tonal tension. Second International Conference on Technologies for Music Notation and Representation (TENOR). 2:8-18.PDF icon paper_tenor_dh_preprint_small.pdf (1.67 MB)
Cunha N., A. S, Herremans D..  2016.  Uma abordagem baseada em programação linear inteira para a geração de solos de guitarra. XLVIII Simpósio Brasileiro de Pesquisa Operacional (SBPO). PDF icon sbpo_dh.pdf (346.61 KB)
Herremans D., Sörensen K..  2013.  Composing Fifth Species Counterpoint Music With A Variable Neighborhood Search Algorithm. Expert Systems with Applications. 40PDF icon paper_preprint_cp5.pdf (405.75 KB)
Herremans D., Martens D, Sörensen K..  2013.  Dance Hit Song Science. International Workshop on Music and Machine Learning. PDF icon abstract_preprint_MML2013_DH.pdf (194.82 KB)
Herremans D., Sörensen K., Conklin D..  2013.  First species counterpoint generation with VNS and vertical viewpoints. Digital Music Research Network (DMNR+8). PDF icon dnmr8_dh_dc.pdf (147.73 KB)
Herremans D., Sörensen K..  2013.  FuX, an Android app that generates counterpoint. IEEE Symposium on Computational Intelligence for Creativity and Affective Computing (CICAC). :48-55.PDF icon wp_fux.pdf (486.27 KB)
Herremans D..  2005.  Tabu Search voor de optimalisatie van muzikale fragmenten. Faculty of Applied Economics. MSc Business Engineer Management Information SystemsPDF icon thesis.pdf (473.77 KB)