Publications

Export 149 results:
Author Title [ Type(Asc)] Year
Journal Article
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)
Kang J, Poria S, Herremans D..  2024.  Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model. Expert Systems with Applications. PDF icon 2311.00968.pdf (5.51 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)
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)
Sockalingam N., Lo K., Teo J., Wei C.C., Chow D., Herremans D., Jun M.L.M., Kurniawan O., Wang Y., Leong P.K.  2025.  Towards the future of education: cyber-physical learning. Discover Education. 4:1–16.
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)
Bhandari K., Roy A., Wang K., Puri G., Colton S., Herremans D..  2025.  Text2midi: Generating Symbolic Music from Captions. Proceedings of AAAI, Philadelphia. PDF icon 2412.16526v2.pdf (569.51 KB)
Melechovsky J., Mehrish A., Roy A., Herremans D..  2025.  SonicMaster: Towards Controllable All-in-One Music Restoration and Mastering. arXiv:2508.03448. PDF icon 2508.03448v2.pdf (3.31 MB)
Huang J, Chia YKen, Yu S, Yee K, Küster D, Krumhuber EG, Herremans D, Roig G..  2022.  Single Image Video Prediction with Auto-Regressive GANs. Sensors. 22:3533.
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)
Lam P., Zhang H., Chen N.F, Sisman B., Herremans D..  2025.  PRESENT: Zero-Shot Text-to-Prosody Control. IEEE Signal Processing Letters. PDF icon 2408.06827v1.pdf (367.55 KB)
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.
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)
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)
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)
Le D-V-T, Bigo L., Keller M., Herremans D..  2025.  Natural Language Processing Methods for Symbolic Music Generation and Information Retrieval: a Survey. ACM Computing Surveys. PDF icon 2402.17467.pdf (1.01 MB)
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)
Zou Y., Herremans D..  2023.  A Multimodal Model with Twitter Finbert Embeddings for Extreme Price Movement Prediction of Bitcoin. Expert Systems with Applications. PDF icon 2206.00648.pdf (3.26 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)
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)
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)
Lu T., Geist C-M, Melechovsky J., Roy A., Herremans D..  2025.  MelodySim: Measuring Melody-aware Music Similarity for Plagiarism Detection. arXiv:2505.20979.
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)
Song M., Pala T.D, Jin W., Zadeh A., Li C., Herremans D., Poria S..  2025.  LLMs Can't Handle Peer Pressure: Crumbling under Multi-Agent Social Interactions. arXiv:2508.18321.
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., 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)
Cunha N., A. S, Herremans D.  2017.  Generating guitar solos by integer programming. Journal of the Operational Research Society. :971-985.PDF icon preprint_guitar_solo_generation_dh.pdf (772.59 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)
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., Low K.W..  2025.  Forecasting Bitcoin Volatility Spikes from Whale Transactions and Cryptoquant Data Using Synthesizer Transformer Models. IEEE Access. 13:117788-117807.PDF icon SSRN-id4247684.pdf (5.05 MB)
Guo R, Herremans D..  2025.  An exploration of controllability in symbolic music infilling. IEEE Access.
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)
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)
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)
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)
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)
Song M., Liu R., Wang X, Jiang Y, Xie P, Huang F, Zhou J, Herremans D., Poria S..  2025.  Demystifying deep search: a holistic evaluation with hint-free multi-hop questions and factorised metrics. arXiv:2510.05137.
Ong J., Herremans D..  2024.  DeepUnifiedMom: Unified Time-series Momentum Portfolio Construction via Multi-Task Learning with Multi-Gate Mixture of Experts. arXiv:2406.08742. PDF icon 2406.08742v1.pdf (1.06 MB)
T BB, Hee HIng, Kapoor S, Teoh OHoe, Teng SShin, Lee KPin, Herremans D, Chen JMing.  2021.  Deep Neural Network Based Respiratory Pathology Classification Using Cough Sounds. Sensors. 21(16):5555.PDF icon 2106.12174.pdf (6.52 MB)
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)
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., Sörensen K..  2012.  Composing first species counterpoint musical scores with a variable neighbourhood search algorithm. Journal of Mathematics and the Arts. 6:169-189.
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.  2015.  Compose ≡ compute. 4OR. 13:335–336.
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)
Luo J., Yang X., Herremans D..  2025.  BandCondiNet: Parallel Transformers-based Conditional Popular Music Generation with Multi-View Features. Expert Systems with Applications. 130059PDF icon 2407.10462v2.pdf (2.6 MB)
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)
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
Kang J., Herremans D..  2025.  Are we there yet? A brief survey of Music Emotion Prediction Datasets, Models and Outstanding Challenges IEEE Transactions on Affective Computing. PDF icon 2406.08809v1.pdf (156.19 KB)
Herremans D.  2021.  aiSTROM - A roadmap for developing a successful AI strategy. IEEE Access.
Conference Proceedings
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)
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., 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)
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)
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.  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., 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., 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., 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)
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., 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)
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., 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)
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., 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..  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)
Conference Paper
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)
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).
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)
Kang J., Herremans D..  2025.  Towards Unified Music Emotion Recognition across Dimensional and Categorical Models.
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)
Roy A., Puri G., Herremans D..  2026.  Text2midi-InferAlign: Improving Symbolic Music Generation with Inference-Time Alignment. ICASSP.
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)
Chopra A., Roy A., Herremans D..  2025.  SonicVerse: Multi-Task Learning for Music Feature-Informed Captioning. Proceedings of the 6th Conference on AI Music Creativity (AIMC 2025), Brussels, Belgium, September 10th - 12th, 2025.
Lam P., Zhang H., Chen N.F, Sisman B., Herremans D..  2024.  SNIPER Training: Variable Sparsity Rate Training For Text-To-Speech. Proc. of IEEE Tencon, Singapore. PDF icon 2211.07283.pdf (435.22 KB)
Wickramasinghe S., Das B., Herremans D..  2025.  Smart Timing for Mining: A Deep Learning Framework for Bitcoin Hardware ROI Prediction. PDF icon 2512.05402v1.pdf (908 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)
Jiang Z., Yeo S., Herremans D., Perrault S..  2026.  Scaffolded Vulnerability: Chatbot-Mediated Reciprocal Self-Disclosure and Need-Supportive Interaction in Couples. Proceedings of CHI.
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)
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)
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., Su L., Herremans D..  2021.  ReconVAT: A Semi-Supervised Automatic Music Transcription Framework for Low-Resource Real-World Data. ACM Multimedia.
Wei M., Modrzejewski M., Sivaraman A., Herremans D..  2025.  Prevailing Research Areas for Music AI in the Era of Foundation Models.
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)
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)
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)
Melechovsky J, Guo Z, Ghosal D, Majumder N, Herremans D, Poria S.  2024.  Mustango: Toward Controllable Text-to-Music Generation. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). pages 8293–8316. PDF icon 2311.08355 (1).pdf (11.38 MB)

Pages