Publications

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Conference Paper
Melechovsky J., Mehrish A., Sisman B., Herremans D..  2022.  Accented Text-to-Speech Synthesis with a Conditional Variational Autoencoder. Arxiv. PDF icon 2211.03316.pdf (3.11 MB)
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)
T. Phuong HThi, BT B, Herremans D., Roig G..  2021.  AttendAffectNet: Self-Attention based Networks for Predicting Affective Responses from Movies. Proceedings of the International Conference on Pattern Recognition (ICPR2020). PDF icon 2010.11188.pdf (7.07 MB)
Clarke C.J., Chowdhury J., BT B, Priyadarshinee P., Lim C.M.Ying, I. Tan FXing, Herremans D., Chen J.M..  2022.  Computationally Efficient Physics Approximating Neural Networks for Highly Nonlinear Maps. 2022 International Conference on Research in Adaptive and Convergent Systems.
Makris D., Guo Z, Kaliakatsos-Papakostas N., Herremans D..  2022.  Conditional Drums Generation using Compound Word Representations. EvoMUSART (EVO*) - Lecture Notes in Computer Science. PDF icon 2202.04464.pdf (525.36 KB)
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. PDF icon 2009.04459.pdf (234.8 KB)
Cheuk K.W., Sawata R, Uesaka T, Murata N, Takahashi N, Takahashi S, Herremans D., Mitsufuji Y.  2023.  DiffRoll: Diffusion-based Generative Music Transcription with Unsupervised Pretraining Capability. ICASSP. PDF icon diffroll.pdf (2.2 MB)
Guo Z, Kang J., Herremans D..  2023.  A Domain-Knowledge-Inspired Music Embedding Space and a Novel Attention Mechanism for Symbolic Music Modeling. Proceedings of the 37th AAAI Conference on Artificial Intelligence. PDF icon 2212.00973.pdf (1.74 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)
Cheuk K.W., Luo Y.J., Benetos E., Herremans D..  2021.  The Effect of Spectrogram Reconstructions on Automatic Music Transcription:An Alternative Approach to Improve Transcription Accuracy. Proceedings of the International Conference on Pattern Recognition (ICPR2020). PDF icon 2010.09969.pdf (3.46 MB)
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)
Makris D., Agres K., Herremans D..  2021.  Generating Lead Sheets with Affect: A Novel Conditional seq2seq Framework. Proceedings of the International Joint Conference on Neural Networks (IJCNN). PDF icon 2104.13056.pdf (857.78 KB)
Turian J, Shier J, Khan HRaj, Raj B, Schuller BW, Steinmetz CJ, Malloy C, Tzanetakis G, Velarde G, McNally K et al..  2022.  HEAR 2021: Holistic Evaluation of Audio Representations. Proceedings of Machine Learning Research (PMLR): NeurIPS 2021 Competition Track. PDF icon 2203.03022.pdf (406.58 KB)
Guo Z, Makris D., Herremans D..  2021.  Hierarchical Recurrent Neural Networks for Conditional Melody Generation with Long-term Structure. Proceedings of the International Joint Conference on Neural Networks (IJCNN). PDF icon 2102.09794.pdf (1015.73 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)
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)
Cheuk K.W., Choi K., Kong Q., Li B., Won M., Hung A., Wang J.-C., Herremans D..  2022.  Jointist: Joint Learning for Multi-instrument Transcription and Its Applications. PDF icon 2206.10805.pdf (427.51 KB)
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)
Melechovsky J., Mehrish A., Herremans D., Sisman B..  2023.  Learning accent representation with multi-level VAE towards controllable speech synthesis. IEEE Spoken Language Technology (SLT) Workshop.
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)
Kaliakatsos-Papakostas N., Bastas G., Makris D., Herremans D., Katsouros V., Maragos P..  2022.  A Machine Learning Approach for MIDI to Guitar Tablature Conversion. Sound and Music Computing Conference (SMC). PDF icon 25.pdf (528.42 KB)
Herremans D., Weisser S., Sörensen K., Conklin D..  2014.  Markov Based Quality Metrics For Generating Structured Music With Optimization Techniques. Digital Music Research Network (DMNR+9). PDF icon dmrn9_dh.pdf (133.29 KB)
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)
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)
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)
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)
Guo R, Simpton I., Kiefer C., Magnusson T, Herremans D..  2022.  MusIAC: An extensible generative framework for Music Infilling Application with multi-level Control. EvoMUSART. PDF icon 2202.05528.pdf (893.23 KB)
Tan H.H., Herremans D..  2020.  Music FaderNets: Controllable Music Generation Based On High-Level Features via Low-Level Feature Modelling. ISMIR. PDF icon 2007.15474.pdf (2.67 MB)
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)
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., Su L., Herremans D..  2021.  ReconVAT: A Semi-Supervised Automatic Music Transcription Framework for Low-Resource Real-World Data. ACM Multimedia.
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)
Cheuk K.W., Luo Y.J., Benetos E., Herremans D..  2021.  Revisiting the Onsets and Frames Model with Additive Attention. Proceedings of the International Joint Conference on Neural Networks (IJCNN). PDF icon 2104.06607.pdf (1.52 MB)
Herremans D., Sörensen K., Conklin D..  2014.  Sampling the extrema from statistical models of music with variable neighbourhood search. ICMC/SMC. PDF icon icmc_dh.pdf (1.07 MB)
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)
Lam P., Zhang H., Chen N.F, Sisman B., Herremans D..  2022.  SNIPER Training: Variable Sparsity Rate Training For Text-To-Speech . Arxiv 2211.07283. PDF icon 2211.07283.pdf (435.22 KB)
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., 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)
Kwan Y.H., Cheuk K.W., Herremans D..  2022.  Understanding Audio Features via Trainable Basis Functions. Arxiv preprint. PDF icon 2204.11437.pdf (7.36 MB)
Luo Y.J., Cheuk K.W., Nakano T., Goto M., Herremans D..  2020.  Unsupervised disentanglement of pitch and timbre for isolated musical instrument sounds. Proceedings of the International Society of Music Information Retrieval (ISMIR).
Guo R, Simpson I, Magnusson T, Kiefer C., Herremans D..  2020.  A variational autoencoder for music generation controlled by tonal tension. Joint Conference on AI Music Creativity (CSMC + MuMe). PDF icon 2010.06230.pdf (622.82 KB)
Conference Proceedings
Herremans D., Sörensen K..  2012.  Composing counterpoint musical scores with variable neighborhood search. Annual Conference of the Belgian Operation Research Society (ORBEL26). PDF icon orbel26abs_vnsforcp.pdf (116.85 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)
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., 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., Conklin D..  2014.  First species counterpoint generation with VNS and vertical viewpoints. Annual Conference of the Belgian Operation Research Society (ORBEL28). PDF icon orbel28_dh.pdf (216.63 KB)
Herremans D., Weisser S., Sörensen K., Conklin D..  2015.  Generating music with an optimization algorithm using a Markov based objective function. ORBEL29, Belgian Conference on Operations Research. PDF icon orbel29abs.pdf (138.67 KB)
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)
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..  2016.  MorpheuS: constraining structure in automatic music generation. Dagstuhl seminar on Computational Music Structure Analysis. PDF icon abstract_dagstuhl_dh.pdf (88.49 KB)
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)
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., 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)
Journal Article
BT B, Hee H.I., Teoh O.H., Lee K.P., Kapoor S., Herremans D., Chen J.M..  2020.  Asthmatic versus healthy child classification based on cough and vocalised /a:/ sounds. The Journal of the Acoustical Society of America (JASA). 148, EL253
T. Phuong HThi, BT B, Roig G., Herremans D..  2021.  AttendAffectNet – Emotion Prediction of Movie Viewers Using Multimodal Fusion with Self-attention. Sensors. Special issue on Intelligent Sensors: Sensor Based Multi-Modal Emotion Recognition. PDF icon sensors-21-08356.pdf (1.03 MB)
Herremans D., Sörensen K., Martens D.  2015.  Classification and generation of composer-specific music using global feature models and variable neighborhood search. Computer Music Journal. 39(3):91.PDF icon papercmj-dh_preprint.pdf (637.63 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., Sörensen K..  2012.  Composing first species counterpoint musical scores with a variable neighbourhood search algorithm. Journal of Mathematics and the Arts. 6:169-189.
Ong J., Herremans D..  2023.  Constructing Time-Series Momentum Portfolios with Deep Multi-Task Learning. Expert Systems with Applications. 230(120587)PDF icon 2306.13661.pdf (707.95 KB)
Herremans D., Martens D, Sörensen K..  2014.  Dance hit song prediction. Journal of New music Research. 43:302.PDF icon wp_hit.pdf (689.07 KB)
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)
Levers O.D, Herremans D., Dipankar A., Blessing L..  2022.  Downscaling using Deep Convolutional Autoencoders, a case study for South East Asia. Egusphere preprint. PDF icon egusphere-2022-234.pdf (8.99 MB)
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)
Pham Q-H, Herremans D., Roig G..  2022.  EmoMV: Affective Music-Video Correspondence Learning Datasets for Classification and Retrieval. Information Fusion. PDF icon SSRN-id4189323.pdf (2.01 MB)
Wang K., Tekler Z., Cheah L., Herremans D., Blessing L..  2021.  Evaluating the Effectiveness of an Augmented Reality Game Promoting Environmental Action. Sustainability. 13(24):13912.PDF icon sustainability-13-13912.pdf (16.23 MB)
Herremans D., Low K.W..  2022.  Forecasting Bitcoin Volatility Spikes from Whale Transactions and Cryptoquant Data Using Synthesizer Transformer Models. SSRN. PDF icon SSRN-id4247684.pdf (5.05 MB)
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)
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)
Herremans D., Weisser S., Sörensen K., Conklin D..  2015.  Generating structured music for bagana using quality metrics based on Markov models. Expert Systems With Applications. 42 (21)(21):424–7435.PDF icon paper-bagana.pdf (1.73 MB)
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)
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)
Koh E., Cheuk K.W., Heung K.Y., Agres K., Herremans D..  2023.  MERP: A Music Dataset with Emotion Ratings and Raters’ Profile Information. Sensors - Intelligent Sensors. 23(1)PDF icon sensors-23-00382 (2).pdf (1.21 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)
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)
Zou Y., Herremans D..  2023.  A Multimodal Model with Twitter Finbert Embeddings for Extreme Price Movement Prediction of Bitcoin. Expert Systems with Applications.
Agres K., Schaefer R, Volk A, Van Hooren S, Holzapfel A, Bella SDalla, Müller M, de Witte M, Herremans D., Melendez RRamirez et al..  2021.  Music, Computing, and Health: A roadmap for the current and future roles of music technology for healthcare and well-being. Music & Science. PDF icon Preprint for OSF_Agres, Schaefer, Volk, et al. (2021)_Music & Science_watermark.pdf (4.07 MB)
Le D-V-T, Bigo L., Keller M., Herremans D..  2024.  Natural Language Processing Methods for Symbolic Music Generation and Information Retrieval: a Survey. arXiv. 2402.17467
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. PDF icon nnAudio.pdf (10.2 MB)
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)
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)
Chua P., Makris D., Agres K., Roig G., Herremans D..  2022.  Predicting emotion from music videos: exploring the relative contribution of visual and auditory information to affective responses. Arxiv preprint.
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)
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)
Lee-Leon A., Yuen C., Herremans D..  2021.  Underwater Acoustic Communication Receiver Using Deep Belief Network. IEEE Transactions on Communications. :1-1.PDF icon 2102.13397.pdf (12.87 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)
Sockalingam N., Lo K., n KO., Herremans D., Raghunath N., Cancion H.GC, Kejun H., Leong H., Tan J., Nizharzharudin K. et al..  2022.  A white paper on cyberphysical learning. White paper, Singapore University of Technology and Design. PDF icon LSL_WhitePaper_Cyber-physical-Campus-Higher-Education.pdf (6.98 MB)

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