Melechovsky J., Mehrish A., Sisman B., Herremans D..  2024.  Accent Conversion in Text-To-Speech Using Multi-Level VAE and Adversarial Training. Proc. of IEEE Tencon, Singapore.

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Melechovsky J., Mehrish A., Sisman B., Herremans D..  2024.  Accented Text-to-Speech Synthesis with a Conditional Variational Autoencoder. Proc. of IEEE Tencon, Singapore.

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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).

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preprint flow.pdf (1.01 MB)

Herremans D.  2021.  aiSTROM - A roadmap for developing a successful AI strategy. IEEE Access.

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Kang J., Herremans D..  2024.  Are we there yet? A brief survey of Music Emotion Prediction Datasets, Models and Outstanding Challenges arXiv:2406.08809.

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2406.08809v1.pdf (156.19 KB)

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

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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.

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sensors-21-08356.pdf (1.03 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).

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2010.11188.pdf (7.07 MB)

Luo J., Yang X., Herremans D..  2024.  BandControlNet: Parallel Transformers-based Steerable Popular Music Generation with Fine-Grained Spatiotemporal Features. arXiv:2407.10462.

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2407.10462v1.pdf (2.3 MB)

Cheuk K.W., BT B, Roig G., Herremans D..  2018.  Blacklisted speaker identification using triplet neural networks. MCE2018 competition.

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SUTD_description.pdf (133.08 KB)

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.

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papercmj-dh_preprint.pdf (637.63 KB)

Lanzendörfer L.A., Lu T., Perraudin N., Herremans D., Wattenhofer R..  2025.  Coarse-to-Fine Text-to-Music Latent Diffusion. ICASSP.

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Lanzendörfer L.A., Lu T., Perraudin N., Herremans D., Wattenhofer R..  2024.  Coarse-to-Fine Text-to-Music Latent Diffusion. Audio Imagination: NeurIPS 2024 Workshop.

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Herremans D.  2015.  Compose ≡ compute. 4OR. 13:335–336.

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Herremans D..  2014.  Compose=Compute - Computer Generation And Classification Of Music Through Operations Research Methods. PhD Thesis, University of Antwerp. :250.

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Herremans D., Martens D, Sörensen K., Meredith D..  2015.  Composer Classification Models for Music-Theory Building. Computational Music Analysis.

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Chapter_HerremansEtAl_preprint.pdf (475.26 KB)

Herremans D., Sörensen K..  2012.  Composing counterpoint musical scores with variable neighborhood search. Annual Conference of the Belgian Operation Research Society (ORBEL26).

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orbel26abs_vnsforcp.pdf (116.85 KB)

Herremans D., Sörensen K..  2013.  Composing Fifth Species Counterpoint Music With A Variable Neighborhood Search Algorithm. Expert Systems with Applications. 40

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paper_preprint_cp5.pdf (405.75 KB)

Herremans D., Sörensen K..  2012.  Composing Fifth Species Counterpoint Music With Variable Neighborhood Search.

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wp_cp5.pdf (508 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.

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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.

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Makris D., Guo Z, Kaliakatsos-Papakostas N., Herremans D..  2022.  Conditional Drums Generation using Compound Word Representations. EvoMUSART (EVO*) - Lecture Notes in Computer Science.

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2202.04464.pdf (525.36 KB)

Ong J., Herremans D..  2023.  Constructing Time-Series Momentum Portfolios with Deep Multi-Task Learning. Expert Systems with Applications. 230(120587)

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2306.13661.pdf (707.95 KB)

Herremans D., Martens D, Sörensen K..  2014.  Dance hit song prediction. Journal of New music Research. 43:302.

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wp_hit.pdf (689.07 KB)

Herremans D., Martens D, Sörensen K..  2013.  Dance Hit Song Science. International Workshop on Music and Machine Learning.

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abstract_preprint_MML2013_DH.pdf (194.82 KB)

Melechovsky J., Mehrish A., Sisman B., Herremans D..  2024.  DART: Disentanglement of Accent and Speaker Representation in Multispeaker Text-to-Speech. Audio Imagination: NeurIPS 2024 Workshop.

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Pham Q-H.  2020.  Data-driven 3D Scene Understanding. PhD

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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.

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2009.04459.pdf (234.8 KB)

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.

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2106.12174.pdf (6.52 MB)

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.

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2406.08742v1.pdf (1.06 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)

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applsci-09-02833.pdf (2.06 MB)

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.

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diffroll.pdf (2.2 MB)

Wang K., Herremans D..  2024.  DisfluencySpeech -- Single-Speaker Conversational Speech Dataset with Paralanguage. Proc. of IEEE Tencon, Singapore.

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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.

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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).

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1909.02850.pdf (790.54 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.

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egusphere-2022-234.pdf (8.99 MB)

Herremans D..  2010.  Drupal 6: Ultimate Community Site Guide.

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Agres K, Bigo L, Herremans D, Conklin D.  2015.  The effect of repetitive structure on enjoyment and altered states in uplifting trance music. 2nd International Conference on Music and Consciousness (MUSCON 2), Brighton.

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AgresEtAl_muscon.pdf (12.47 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.

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preprint_trance.pdf (139.27 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).

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2010.09969.pdf (3.46 MB)

Herremans D., Chuan C.-H..  2019.  The emergence of deep learning: new opportunities for music and audio technologies. Neural Computing and Applications.

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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.

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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.

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sustainability-13-13912.pdf (16.23 MB)

Guo R, Herremans D..  2025.  An exploration of controllability in symbolic music infilling. IEEE Access.

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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).

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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).

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dnmr8_dh_dc.pdf (147.73 KB)

Herremans D., Low K.W..  2022.  Forecasting Bitcoin Volatility Spikes from Whale Transactions and Cryptoquant Data Using Synthesizer Transformer Models. SSRN.

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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.

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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.

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music_generation_survey_dh_preprint.pdf (349.15 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.

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wp_fux.pdf (486.27 KB)

Chow D., Herremans D..  2024.  Gamification and skills tree. Trends and Foresight Report on Cyber-Physical Learning.

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BT B, Hee H.I., Ming C., Lin Y., Priyadarshinee P., Clarke C.J., Herremans D., Chen J.M..  2022.  A Gaussian mixture classifier model to differentiate respiratory symptoms using phonated /ɑː/ sounds. The 18th Australasian International Conference on Speech Science and Technology (SST).

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ahsounds.pdf (1018.01 KB)

Balliauw M., Herremans D., D. Cuervo P, Sörensen K..  2015.  Generating Fingerings for Polyphonic Piano Music with a Tabu Search Algorithm. Mathematics and Computation in Music. 9110:149-160.

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paper_mcm_preprint.pdf (405.73 KB)

Cunha N., A. S, Herremans D.  2017.  Generating guitar solos by integer programming. Journal of the Operational Research Society. :971-985.

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preprint_guitar_solo_generation_dh.pdf (772.59 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).

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2104.13056.pdf (857.78 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.

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orbel29abs.pdf (138.67 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.

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paper-bagana.pdf (1.73 MB)

Herremans D., Weisser S., Sörensen K., Conklin D..  2014.  Generating structured music using quality metrics based on Markov models.

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wp_bagana.pdf (1.7 MB)

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.

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2006.09833.pdf (2.81 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)

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agres16ut.pdf (1.15 MB)

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.

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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).

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2102.09794.pdf (1015.73 KB)

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.

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paper_preprint_hit.pdf (221.73 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.

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fuzzy logic.pdf (1.66 MB)

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.

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IMMA-emo_preprint.pdf (1.4 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).

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2001.09989.pdf (1.87 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.

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Bhandari K., Chang S., Lu T., Enus F.R, Bradshaw L.B, Herremans D., Colton S..  2025.  ImprovNet: Generating Controllable Musical Improvisations with Iterative Corruption Refinement.

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Roy A., Liu R., Lu T., Herremans D..  2025.   JamendoMaxCaps: A Large Scale Music-caption Dataset with Imputed Metadata.

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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.

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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).

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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.

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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.

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jyun-ismir.pdf (5.62 MB)

Liu R., Roy A., Herremans D..  2025.  Leveraging LLM Embeddings for Cross Dataset Label Alignment and Zero Shot Music Emotion Prediction.

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Herremans D., Martens D, Sörensen K..  2014.  Looking into the minds of Bach, Haydn and Beethoven: Classification and generation of composer-specific music.

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RPS-2014-001.pdf (575.42 KB)

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).

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25.pdf (528.42 KB)

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.

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concert_paper_preprint.pdf (1.6 MB)

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).

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dmrn9_dh.pdf (133.29 KB)

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)

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sensors-23-00382 (2).pdf (1.21 MB)

Guo R, Herremans D, Magnusson T.  2019.  Midi Miner – A Python library for tonal tension and track classification. ISMIR - Late Breaking Demo.

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midi_miner.pdf (83.7 KB)

Melechovsky J., Roy A., Herremans D..  2024.  MidiCaps — A large-scale MIDI dataset with text captions. ISMIR.

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2406.02255v1.pdf (699.83 KB)

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.

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angus_jaes_preprint.pdf (6.39 MB)

Chopra A., Roy A., Herremans D..  2024.  MIRFLEX: Music Information Retrieval Feature Library for Extraction. ISMIR, Late Breaking Demos.

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2411.00469v1.pdf (89.86 KB)

Herremans D., Chuan C.-H..  2017.  Modeling Musical Context with Word2vec. First International Workshop On Deep Learning and Music. 1:11-18.

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herremans2017work2vec.pdf (745.8 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.

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preprint_lstm.pdf (741.28 KB)

Ong J..  2024.  Modern Portfolio Construction with Advanced Deep Learning Models. SUTD. PhD

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Joel_Ong_Thesis.pdf (3.44 MB)

Herremans D., Chew E..  2016.  MorpheuS: Automatic music generation with recurrent pattern constraints and tension profiles. IEEE TENCON.

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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.

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abstract_dagstuhl_dh.pdf (88.49 KB)

Herremans D., Chew E..  2017.  MorpheuS: generating structured music with constrained patterns and tension. IEEE Transactions on Affective Computing. PP (In Press)(99)

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herremans2017morpheusFullIEEE.pdf (5.71 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.

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1909.06957.pdf (836.3 KB)

Zou Y., Herremans D..  2023.  A Multimodal Model with Twitter Finbert Embeddings for Extreme Price Movement Prediction of Bitcoin. Expert Systems with Applications.

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2206.00648.pdf (3.26 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.

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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.

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2202.05528.pdf (893.23 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) .

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agres_herr_music_rehab_preprint.pdf (1.77 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.

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Preprint for OSF_Agres, Schaefer, Volk, et al. (2021)_Music & Science_watermark.pdf (4.07 MB)

Tan H.H., Herremans D..  2020.  Music FaderNets: Controllable Music Generation Based On High-Level Features via Low-Level Feature Modelling. ISMIR.

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2007.15474.pdf (2.67 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.

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orbel30_dh.pdf (117.78 KB)

Kroonenberg P., Herremans D..  2021.  Musical stylometry: Characterisation of music. Multivariate Humanities.

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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.

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2311.08355 (1).pdf (11.38 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.

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2402.17467.pdf (1.01 MB)