Publications

2025

  1. Are we there yet? A brief survey of Music Emotion Prediction Datasets, Models and Outstanding Challenges
    Kang, J. and Herremans, D.
    IEEE Transactions on Affective Computing , 2025
    Paper
  2. Coarse-to-Fine Text-to-Music Latent Diffusion
    Lanzendörfer, L.A. and Lu, T. and Perraudin, N. and Herremans, D. and Wattenhofer, R.
    Proceedings of ICASSP , 2025
    Paper
  3. End-to-End Text-to-SQL with Dataset Selection: Leveraging LLMs for Adaptive Query Generation
    Tripathi, A. and Patle, V. and Jain, A. and Pundir, A. and Menon, S. and Singh, A. Kumar and Herremans, D.
    Proceedings of IJCNN, Rome, Italy , 2025
    Paper
  4. An exploration of controllability in symbolic music infilling
    Guo, Rui and Herremans, D.
    IEEE Access , 2025
    Paper DOI
  5. Forecasting Bitcoin Volatility Spikes from Whale Transactions and Cryptoquant Data Using Synthesizer Transformer Models
    Herremans, D. and Low, K.W.
    IEEE Access , vol. 13 , pp. 117788-117807 , 2025
    Paper DOI
  6. ImprovNet: Generating Controllable Musical Improvisations with Iterative Corruption Refinement
    Bhandari, K. and Chang, S. and Lu, T. and Enus, F. R. and Bradshaw, L. B. and Herremans, D. and Colton, S.
    Proceedings of IJCNN, Rome, Italy , 2025
    Paper
  7. JamendoMaxCaps: A Large Scale Music-caption Dataset with Imputed Metadata
    Roy, A. and Liu, R. and Lu, T. and Herremans, D.
    Proceedings of IJCNN, Rome, Italy , 2025
    Paper
  8. Leveraging LLM Embeddings for Cross Dataset Label Alignment and Zero Shot Music Emotion Prediction
    Liu, R. and Roy, A. and Herremans, D.
    arXiv preprint , 2025
    Paper
  9. LLMs Can’t Handle Peer Pressure: Crumbling under Multi-Agent Social Interactions
    Song, M. and Pala, T. D. and Jin, W. and Zadeh, A. and Li, C. and Herremans, D. and Poria, S.
    arXiv preprint , 2025
    Paper
  10. MelodySim: Measuring Melody-aware Music Similarity for Plagiarism Detection
    Lu, T. and Geist, C-M and Melechovsky, J. and Roy, A. and Herremans, D.
    arXiv preprint , 2025
    Paper
  11. Natural Language Processing Methods for Symbolic Music Generation and Information Retrieval: a Survey
    Le, Dinh-Viet-Toan and Bigo, L. and Keller, M. and Herremans, D.
    ACM Computing Surveys , 2025
    Paper DOI
  12. PRESENT: Zero-Shot Text-to-Prosody Control
    Lam, P. and Zhang, H. and Chen, N. F. and Sisman, B. and Herremans, D.
    IEEE Signal Processing Letters , 2025
    Paper DOI
  13. Prevailing Research Areas for Music AI in the Era of Foundation Models
    Wei, M. and Modrzejewski, M. and Sivaraman, A. and Herremans, D.
    arXiv preprint , 2025
    Paper
  14. Royalties in the age of AI: paying artists for AI-generated songs
    Herremans, D.
    WIPO magazine , 2025
    Paper
  15. SonicMaster: Towards Controllable All-in-One Music Restoration and Mastering
    Melechovsky, J. and Mehrish, A. and Herremans, D.
    arXiv preprint , 2025
    Paper
  16. SonicVerse: Multi-Task Learning for Music Feature-Informed Captioning
    Chopra, A. and Roy, A. and Herremans, D.
    Proceedings of the 6th Conference on AI Music Creativity (AIMC 2025), Brussels, Belgium, September 10th - 12th, 2025 , 2025
    Paper
  17. Text2midi: Generating Symbolic Music from Captions
    Bhandari, K. and Roy, A. and Wang, K. and Puri, G. and Colton, S. and Herremans, D.
    Proceedings of AAAI, Philadelphia , 2025
    Paper
  18. Text2midi-InferAlign: Improving Symbolic Music Generation with Inference-Time Alignment
    Roy, A. and Puri, G. and Herremans, D.
    arXiv preprint , 2025
    Paper
  19. Towards the future of education: cyber-physical learning
    Sockalingam, N. and Lo, K. and Teo, Ju. and Wei, C.C. and Chow, D. and Herremans, D. and Jun, M.L.M. and Kurniawan, O. and Wang, Y. and Leong, P. K.
    Discover Education , vol. 4 , pp. 1–16 , 2025
    Paper DOI
  20. Towards Unified Music Emotion Recognition across Dimensional and Categorical Models
    Kang, J. and Herremans, D.
    arXiv preprint , 2025
    Paper


2024

  1. Accent Conversion in Text-To-Speech Using Multi-Level VAE and Adversarial Training
    Melechovsky, J. and Mehrish, A. and Sisman, B. and Herremans, D.
    Proc. of IEEE Tencon, Singapore , 2024
    Paper
  2. Accented Text-to-Speech Synthesis with a Conditional Variational Autoencoder
    Melechovsky, J. and Mehrish, A. and Sisman, B. and Herremans, D.
    Proc. of IEEE Tencon, Singapore , 2024
    Paper
  3. BandControlNet: Parallel Transformers-based Steerable Popular Music Generation with Fine-Grained Spatiotemporal Features
    Luo, J. and Yang, X. and Herremans, D.
    arXiv preprint , 2024
    Paper
  4. Coarse-to-Fine Text-to-Music Latent Diffusion
    Lanzendörfer, L.A. and Lu, T. and Perraudin, N. and Herremans, D. and Wattenhofer, R.
    Audio Imagination: NeurIPS 2024 Workshop , 2024
  5. DART: Disentanglement of Accent and Speaker Representation in Multispeaker Text-to-Speech
    Melechovsky, J. and Mehrish, A. and Sisman, B. and Herremans, D.
    Audio Imagination: NeurIPS 2024 Workshop , 2024
    Paper
  6. DeepUnifiedMom: Unified Time-series Momentum Portfolio Construction via Multi-Task Learning with Multi-Gate Mixture of Experts
    Ong, J. and Herremans, D.
    arXiv preprint , 2024
    Paper
  7. DisfluencySpeech – Single-Speaker Conversational Speech Dataset with Paralanguage
    Wang, K. and Herremans, D.
    Proc. of IEEE Tencon, Singapore , 2024
    Paper
  8. Gamification and skills tree
    Chow, D. and Herremans, D.
    Trends and Foresight Report on Cyber-Physical Learning , 2024
    Paper
  9. MidiCaps — A large-scale MIDI dataset with text captions
    Melechovsky, J. and Roy, A. and Herremans, D.
    ISMIR , 2024
    Paper
  10. MIRFLEX: Music Information Retrieval Feature Library for Extraction
    Chopra, A. and Roy, A. and Herremans, D.
    ISMIR, Late Breaking Demos , 2024
    Paper
  11. Modern Portfolio Construction with Advanced Deep Learning Models
    Ong, J.
    , vol. PhD , 2024
  12. Mustango: Toward Controllable Text-to-Music Generation
    Melechovsky, Jan and Guo, Zixun and Ghosal, Deepanway and Majumder, Navonil and Herremans, Dorien and Poria, Soujanya
    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 , 2024
    Paper DOI
  13. SNIPER Training: Variable Sparsity Rate Training For Text-To-Speech
    Lam, P. and Zhang, H. and Chen, N. F. and Sisman, B. and Herremans, D.
    Proc. of IEEE Tencon, Singapore , 2024
    Paper
  14. Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model
    Kang, Jaeyong and Poria, Soujanya and Herremans, D.
    Expert Systems with Applications , 2024
    Paper DOI


2023

  1. Constructing Time-Series Momentum Portfolios with Deep Multi-Task Learning
    Ong, J. and Herremans, D.
    Expert Systems with Applications , vol. 230 , 2023
    Paper DOI
  2. DiffRoll: Diffusion-based Generative Music Transcription with Unsupervised Pretraining Capability
    Cheuk, K.W. and Sawata, Ryosuke and Uesaka, Toshimitsu and Murata, Naoki and Takahashi, Naoya and Takahashi, Shusuke and Herremans, D. and Mitsufuji, Yuki
    ICASSP , 2023
  3. A Domain-Knowledge-Inspired Music Embedding Space and a Novel Attention Mechanism for Symbolic Music Modeling
    Guo, Zixun and Kang, J. and Herremans, D.
    Proceedings of the 37th AAAI Conference on Artificial Intelligence , 2023
  4. Learning accent representation with multi-level VAE towards controllable speech synthesis
    Melechovsky, J. and Mehrish, A. and Herremans, D. and Sisman, B.
    IEEE Spoken Language Technology (SLT) Workshop , 2023
  5. MERP: A Music Dataset with Emotion Ratings and Raters’ Profile Information
    Koh, E. and Cheuk, K.W. and Heung, K.Y. and Agres, K. and Herremans, D.
    Sensors - Intelligent Sensors , vol. 23 , 2023
    Paper DOI
  6. A Multimodal Model with Twitter Finbert Embeddings for Extreme Price Movement Prediction of Bitcoin
    Zou, Y. and Herremans, D.
    Expert Systems with Applications , 2023
    Paper DOI


2022

  1. Computationally Efficient Physics Approximating Neural Networks for Highly Nonlinear Maps
    Clarke, C.J. and Chowdhury, J. and BT, Balamurali and Priyadarshinee, P. and Lim, C.M. Ying and Tan, I. Fu Xing and Herremans, D. and Chen, J.M.
    2022 International Conference on Research in Adaptive and Convergent Systems , 2022
    Paper DOI
  2. Conditional Drums Generation using Compound Word Representations
    Makris, D. and Guo, Zixun and Kaliakatsos-Papakostas, N. and Herremans, D.
    EvoMUSART (EVO*) - Lecture Notes in Computer Science , 2022
  3. Downscaling using Deep Convolutional Autoencoders, a case study for South East Asia
    Levers, O. D. and Herremans, D. and Dipankar, A. and Blessing, L.
    Egusphere preprint , 2022
    Paper DOI
  4. EmoMV: Affective Music-Video Correspondence Learning Datasets for Classification and Retrieval
    Pham, Quang-Hieu and Herremans, D. and Roig, G.
    Information Fusion , 2022
    Paper DOI
  5. A Gaussian mixture classifier model to differentiate respiratory symptoms using phonated /ɑ:/ sounds
    BT, Balamurali and Hee, H.I. and Ming, C. and Lin, Y. and Priyadarshinee, P. and Clarke, C.J. and Herremans, D. and Chen, J.M.
    The 18th Australasian International Conference on Speech Science and Technology (SST) , 2022
    Paper
  6. HEAR 2021: Holistic Evaluation of Audio Representations
    Turian, Joseph and Shier, Jordie and Khan, Humair Raj and Raj, Bhiksha and Schuller, Björn W. and Steinmetz, Christian J. and Malloy, Colin and Tzanetakis, George and Velarde, Gissel and McNally, Kirk and Henry, Max and Pinto, Nicolas and Noufi, Camille and Clough, Christian and Herremans, D. and Fonseca, Eduardo and Engel, Jesse and Salamon, Justin and Esling, Philippe and Manocha, Pranay and Watanabe, Shinji and Jin, Zeyu and Bisk, Yonatan
    Proceedings of Machine Learning Research (PMLR): NeurIPS 2021 Competition Track , 2022
    Paper
  7. Jointist: Joint Learning for Multi-instrument Transcription and Its Applications
    Cheuk, K.W. and Choi, K. and Kong, Q. and Li, B. and Won, M. and Hung, A. and Wang, J.-C. and Herremans, D.
    arXiv preprint , 2022
    Paper DOI
  8. A Machine Learning Approach for MIDI to Guitar Tablature Conversion
    Kaliakatsos-Papakostas, N. and Bastas, G. and Makris, D. and Herremans, D. and Katsouros, V. and Maragos, P.
    Sound and Music Computing Conference (SMC) , 2022
  9. MusIAC: An extensible generative framework for Music Infilling Application with multi-level Control
    Guo, Rui and Simpton, I. and Kiefer, C. and Magnusson, Thor and Herremans, D.
    EvoMUSART , 2022
    Paper
  10. Predicting emotion from music videos: exploring the relative contribution of visual and auditory information to affective responses
    Chua, P. and Makris, D. and Agres, K. and Roig, G. and Herremans, D.
    arXiv preprint , 2022
    Paper
  11. Single Image Video Prediction with Auto-Regressive GANs
    Huang, Jiahui and Chia, Yew Ken and Yu, Samson and Yee, Kevin and Küster, Dennis and Krumhuber, Eva G. and Herremans, D and Roig, G.
    Sensors , vol. 22 , pp. 3533 , 2022
    Paper DOI
  12. Understanding Audio Features via Trainable Basis Functions
    Kwan, Y.H. and Cheuk, K.W. and Herremans, D.
    arXiv preprint , 2022
    Paper
  13. A white paper on cyberphysical learning
    Sockalingam, N. and Lo, K. and n, KurniawaO. and Herremans, D. and Raghunath, N. and Cancion, H. G.C. and Kejun, H. and Leong, H. and Tan, J. and Nizharzharudin, K. and Pey, K.L.
    White paper, Singapore University of Technology and Design , 2022
    Paper


2021

  1. aiSTROM - A roadmap for developing a successful AI strategy
    Herremans, D
    IEEE Access , 2021
    Paper DOI
  2. AttendAffectNet – Emotion Prediction of Movie Viewers Using Multimodal Fusion with Self-attention
    Phuong, T. Ha Thi and BT, Balamurali and Roig, G. and Herremans, D.
    Sensors. Special issue on Intelligent Sensors: Sensor Based Multi-Modal Emotion Recognition , 2021
    Paper DOI
  3. AttendAffectNet: Self-Attention based Networks for Predicting Affective Responses from Movies
    Phuong, T. Ha Thi and BT, Balamurali and Herremans, D. and Roig, G.
    Proceedings of the International Conference on Pattern Recognition (ICPR2020) , 2021
  4. Deep Neural Network Based Respiratory Pathology Classification Using Cough Sounds
    T, Balamurali B and Hee, Hwan Ing and Kapoor, Saumitra and Teoh, Oon Hoe and Teng, Sung Shin and Lee, Khai Pin and Herremans, Dorien and Chen, Jer Ming
    Sensors , vol. 21 , pp. 5555 , 2021
    Paper DOI
  5. The Effect of Spectrogram Reconstructions on Automatic Music Transcription:An Alternative Approach to Improve Transcription Accuracy
    Cheuk, K.W. and Luo, Y.J. and Benetos, E. and Herremans, D.
    Proceedings of the International Conference on Pattern Recognition (ICPR2020) , 2021
  6. Evaluating the Effectiveness of an Augmented Reality Game Promoting Environmental Action
    Wang, K. and Tekler, Z. and Cheah, L. and Herremans, D. and Blessing, L.
    Sustainability , vol. 13 , pp. 13912 , 2021
    Paper DOI
  7. Generating Lead Sheets with Affect: A Novel Conditional seq2seq Framework
    Makris, D. and Agres, K. and Herremans, D.
    Proceedings of the International Joint Conference on Neural Networks (IJCNN) , 2021
    Paper
  8. Hierarchical Recurrent Neural Networks for Conditional Melody Generation with Long-term Structure
    Guo, Zixun and Makris, D. and Herremans, D.
    Proceedings of the International Joint Conference on Neural Networks (IJCNN) , 2021
    Paper
  9. Music, Computing, and Health: A roadmap for the current and future roles of music technology for healthcare and well-being
    Agres, K. and Schaefer, Rebecca and Volk, Anja and Van Hooren, Susan and Holzapfel, André and Dalla Bella, Simone and Müller, Meinard and de Witte, Martina and Herremans, D. and Ramirez Melendez, Rafael and Neerincx, Mark and Ruiz, Sebastian and Meredith, David and Dimitriadis, Theo and Magee, Wendy
    Music & Science , 2021
    Paper DOI
  10. Musical stylometry: Characterisation of music
    Kroonenberg, P. and Herremans, D.
    Multivariate Humanities , 2021
    Paper DOI
  11. ReconVAT: A Semi-Supervised Automatic Music Transcription Framework for Low-Resource Real-World Data
    Cheuk, K.W. and Su, L. and Herremans, D.
    ACM Multimedia , 2021
    Paper
  12. Revisiting the Onsets and Frames Model with Additive Attention
    Cheuk, K.W. and Luo, Y.J. and Benetos, E. and Herremans, D.
    Proceedings of the International Joint Conference on Neural Networks (IJCNN) , 2021
  13. Underwater Acoustic Communication Receiver Using Deep Belief Network
    Lee-Leon, A. and Yuen, C. and Herremans, D.
    IEEE Transactions on Communications , pp. 1-1 , 2021
    Paper DOI


2020

  1. Acoustic prediction of flowrate: varying liquid jet stream onto a free surface
    BT, Balamurali and Aslim, E. J. and Ng, Yun Shu Lynn and Kuo, Tricia Li Chuen and Chen, Jacob Shihang and Herremans, D. and Ng, Lay Guat and Chen, J.M.
    IEEE International Conference on Signal Processing and Communications (SPCOM) , 2020
  2. Asthmatic versus healthy child classification based on cough and vocalised /a:/ sounds
    BT, Balamurali and Hee, H.I. and Teoh, O.H. and Lee, K.P. and Kapoor, S. and Herremans, D. and Chen, J.M.
    The Journal of the Acoustical Society of America (JASA) , vol. 148, EL253 , 2020
    Paper DOI
  3. Data-driven 3D Scene Understanding
    Pham, Quang-Hieu
    , vol. PhD , 2020
  4. A dataset and classification model for Malay, Hindi, Tamil and Chinese music
    Nahar, F. and Agres, K. and BT, Balamurali and Herremans, D.
    13th Workshop on music and machine learning (MML) as part of ECML/PKDD , 2020
  5. Generative Modelling for Controllable Audio Synthesis of Expressive Piano Performance
    Tan, Hao Hao and Luo, Y.J. and Herremans, D.
    arXiv preprint , 2020
    Paper
  6. The impact of Audio input representations on neural network based music transcription
    Cheuk, K.W. and Agres, K. and Herremans, D.
    Proceedings of the International Joint Conference on Neural Networks (IJCNN) , 2020
    Paper
  7. Music FaderNets: Controllable Music Generation Based On High-Level Features via Low-Level Feature Modelling
    Tan, H.H. and Herremans, D.
    ISMIR , 2020
  8. nnAudio: An on-the-fly GPU Audio to Spectrogram Conversion Toolbox Using 1D Convolution Neural Networks
    Cheuk, K.W. and Anderson, H. and Agres, K. and Herremans, D.
    IEEE Access , 2020
    Paper DOI
  9. PerceptionGAN: Real-world image construction from provided text through perceptual understanding
    Garg, K. and Singh, A. and Herremans, D. and Lall, B.
    4th Int. Conf. on Imaging, Vision and Pattern Recognition (IVPR), and 9th Int. Conf. on Informatics, Electronics & Vision (ICIEV) , 2020
  10. Regression-based music emotion prediction using triplet neural networks
    Cheuk, K.W. and Luo, Y.J. and BT, Balamurali and Roig, G. and Herremans, D.
    Proceedings of the International Joint Conference on Neural Networks (IJCNN) , 2020
    Paper
  11. Singing voice conversion with disentangled representations of singer and vocal technique using variational autoencoders
    Luo, Y.J. and Hsu, C.-C. and Agres, K. and Herremans, D.
    IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) , 2020
    Paper
  12. Unsupervised disentanglement of pitch and timbre for isolated musical instrument sounds
    Luo, Y.J. and Cheuk, K.W. and Nakano, T. and Goto, M. and Herremans, D.
    Proceedings of the International Society of Music Information Retrieval (ISMIR) , 2020
    Paper
  13. A variational autoencoder for music generation controlled by tonal tension
    Guo, Rui and Simpson, Ivor and Magnusson, Thor and Kiefer, C. and Herremans, D.
    Joint Conference on AI Music Creativity (CSMC + MuMe) , 2020
    Paper


2019

  1. Development of Machine Learning for asthmatic and healthy voluntary cough - a proof of concept study
    Hee, H.I. and BT, Balamurali and Karunakaran, A. and Herremans, D. and Teoh, O.H. and Lee, K.P. and Teng, S.S. and Lui, S. and Chen, J.M.
    Applied Sciences , vol. 9 , 2019
    Paper DOI
  2. Doppler Invariant Demodulation for Shallow Water Acoustic Communications Using Deep Belief Networks
    Lee-Leon, A. and Yuen, C. and Herremans, D.
    16th IEEE Asia Pacific Wireless Communications Symposium (APWCS) , 2019
  3. The emergence of deep learning: new opportunities for music and audio technologies
    Herremans, D. and Chuan, C.-H.
    Neural Computing and Applications , 2019
    Paper DOI
  4. A Hybrid Fuzzy Logic-Neural Network Approach For Multi-path Separation Of Underwater Acoustic Signals
    Lee-Leon, A. and Yuen, C. and Herremans, D.
    89th IEEE Vehicular Technology Conference , 2019
    Paper DOI
  5. The impact of musical structure on enjoyment and absorptive listening states in trance music
    Agres, K. and Bigo, L. and Herremans, D.
    Music and Consciousness 2 - Worlds, Practices, Modalities , 2019
    Paper
  6. Latent space representation for multi-target speaker detection and identification with a sparse dataset using Triplet neural networks
    Cheuk, K.W. and BT, Balamurali and Roig, G. and Herremans, D.
    IEEE Automatic Speech Recognition and Understanding Workshop (ASRU 2019) , 2019
  7. Learning Disentangled Representations of Timbre and Pitch for Musical Instrument Sounds Using Gaussian Mixture Variational Autoencoders
    Luo, Y.J. and Agres, K. and Herremans, D.
    ISMIR , 2019
    Paper
  8. Machine Learning Research that Matters for Music Creation: A Case Study
    Sturm, B. and Ben-Tal, O. and Monaghan, U. and Collins, N. and Herremans, D. and Chew, E. and Hadjeres, G. and Deruty, E. and Pachet, F.
    Journal of New Music Research , vol. 48 , pp. 36-55 , 2019
    DOI
  9. Midi Miner – A Python library for tonal tension and track classification
    Guo, Rui and Herremans, Dorien and Magnusson, Thor
    ISMIR - Late Breaking Demo , 2019
  10. Multimodal Deep Models for Predicting Affective Responses Evoked by Movies
    Phuong, T. Ha Thi and Herremans, D. and Roig, G.
    The 2nd International Workshop on Computer Vision for Physiological Measurement as part of ICCV. Seoul, South Korea. 2019 , 2019
  11. nnAudio: A PyTorch Audio Processing Tool Using 1D Convolution neural networks
    Cheuk, K.W. and Agres, K. and Herremans, D.
    ISMIR - Late Breaking Demo , 2019
  12. A novel music-based game with motion capture to support cognitive and motor function in the elderly
    Agres, K. and Lui, S. and Herremans, D.
    IEEE Conference on Games , 2019
  13. Towards emotion based music generation: A tonal tension model based on the spiral array
    Herremans, D. and Chew, E.
    Proceedings of Cognitive Science (CogSci) , 2019
  14. Towards robust audio spoofing detection: a detailed comparison of traditional and learned features
    BT, Balamurali and Lin, K.W.E. and Lui, S. and Chen, J.M. and Herremans, D.
    IEEE Access , vol. 7 , pp. 84229 - 84241 , 2019
    Paper DOI


2018

  1. Blacklisted speaker identification using triplet neural networks
    Cheuk, K.W. and BT, Balamurali and Roig, G. and Herremans, D.
    MCE2018 competition , 2018
    Paper
  2. From Context to Concept: Exploring Semantic Relationships in Music with Word2Vec
    Chuan, C.-H. and Agres, K. and Herremans, D.
    Neural Computing and Applications , 2018
    Paper DOI
  3. Minimally Simple Binaural Room Modelling Using a Single Feedback Delay Network
    Agus, N. and Anderson, H. and Chen, J.M. and Lui, S. and Herremans, D.
    Journal of the Audio Engineering Society , vol. 66 , pp. 791-807 , 2018
    DOI
  4. Modeling temporal tonal relations in polyphonic music through deep networks with a novel image-based representation
    Chuan, C.-H. and Herremans, D.
    The Thirty-Second AAAI Conference on Artificial Intelligence , 2018
  5. A Novel Interface for the Graphical Analysis of Music Practice Behaviours
    Sokolovskis, J. and Herremans, D. and Chew, E.
    Frontiers in Psychology - Human-Media Interaction , vol. 9 , 2018
    Paper DOI
  6. O.R. and music generation
    Herremans, D. and Chew, E.
    OR/MS Today , vol. 45 , 2018
    Paper
  7. Perceptual evaluation of measures of spectral variance
    Agus, N. and Anderson, H. and Chen, J.M. and Lui, S. and Herremans, D.
    Journal of the Acoustical Society of America , vol. 143 , pp. 3300–3311 , 2018
    Paper DOI
  8. Real-Time Binaural Auralization
    Agus, N.
    , vol. PhD , 2018
  9. Singing Voice Separation Using a Deep Convolutional Neural Network Trained by Ideal Binary Mask and Cross Entropy
    Lin, K.W.E. and BT, Balamurali and Koh, E. and Lui, S. and Herremans, D.
    Neural Computing and Applications , 2018
    Paper DOI
  10. The Structure of Chord Progressions Influences Listeners’ Enjoyment and Absorptive States in EDM
    Agres, K. and Herremans, D.
    15th International Conference on Music Perception and Cognition , 2018


2017

  1. A Functional Taxonomy of Music Generation Systems
    Herremans, D. and Chuan, C.-H. and Chew, E.
    ACM Computing Surveys , vol. 50 , pp. 30 , 2017
    Paper DOI
  2. Generating guitar solos by integer programming
    Cunha, N. and A., Subramanian and Herremans, D
    Journal of the Operational Research Society , pp. 971-985 , 2017
    Paper DOI
  3. Harmonic Structure Predicts the Enjoyment of Uplifting Trance Music
    Agres, K. and Herremans, D. and Bigo, L. and Conklin, D.
    Frontiers in Psychology, Cognitive Science , vol. 7 , 2017
    Paper
  4. Hit Song Prediction Based on Early Adopter Data and Audio Features
    Herremans, D. and Bergmans, T.
    ISMIR , 2017
  5. IMMA-Emo: A Multimodal Interface for Visualising Score- and Audio-synchronised Emotion Annotations
    Herremans, D. and Yang, S. and Chuan, C.-H. and Barthet, M. and Chew, E.
    Audio Mostly , 2017
  6. Modeling Musical Context with Word2vec
    Herremans, D. and Chuan, C.-H.
    First International Workshop On Deep Learning and Music , vol. 1 , pp. 11-18 , 2017
    Paper DOI
  7. MorpheuS: generating structured music with constrained patterns and tension
    Herremans, D. and Chew, E.
    IEEE Transactions on Affective Computing , vol. PP (In Press) , 2017
    DOI
  8. A multi-modal platform for semantic music analysis: visualizing audio- and score-based tension
    Herremans, D. and Chuan, C.-H.
    11th International Conference on Semantic Computing IEEE ICSC 2017 , 2017
  9. Music and Motion-Detection: A Game Prototype for Rehabilitation and Strengthening in the Elderly
    Agres, K. and Herremans, D.
    IEEE International Conference on Orange Technologies (ICOT) , 2017
  10. A variable neighborhood search algorithm to generate piano fingerings for polyphonic sheet music
    Balliauw, M. and Herremans, D. and Palhazi Cuervo, D. and Sörensen, K.
    International Transactions in Operational Research, Special Issue on Variable Neighbourhood Search , vol. 24 , pp. 509–535 , 2017
    Paper DOI
  11. Visualizing the evolution of alternative hit charts
    Herremans, D. and Lauwers, W.
    ISMIR , 2017


2016

  1. The Effect of Repetitive Structure on Enjoyment in Uplifting Trance Music
    Agres, K. and Bigo, L. and Herremans, D. and Conklin, D.
    14th International Conference for Music Perception and Cognition (ICMPC) , pp. 280-282 , 2016
  2. MorpheuS: Automatic music generation with recurrent pattern constraints and tension profiles
    Herremans, D. and Chew, E.
    IEEE TENCON (ISSN 2043-0167) , 2016
  3. MorpheuS: constraining structure in automatic music generation
    Herremans, D. and Chew, E.
    Dagstuhl seminar on Computational Music Structure Analysis , 2016
    Paper
  4. Music generation with structural constraints: an operations research approach
    Herremans, D. and Chew, E.
    30th Annual Conference of the Belgian Operational Research (OR) Society (ORBEL30) , pp. 37-39 , 2016
  5. Tension ribbons: Quantifying and visualising tonal tension
    Herremans, D. and Chew, E.
    Second International Conference on Technologies for Music Notation and Representation (TENOR) , vol. 2 , pp. 8-18 , 2016
  6. Uma abordagem baseada em programação linear inteira para a geração de solos de guitarra
    Cunha, N. and A., Subramanian and Herremans, D.
    XLVIII Simpósio Brasileiro de Pesquisa Operacional (SBPO) , 2016


2015

  1. Classification and generation of composer-specific music using global feature models and variable neighborhood search
    Herremans, D. and Sörensen, K. and Martens, David
    Computer Music Journal , vol. 39 , pp. 91 , 2015
  2. Compose = compute
    Herremans, Dorien
    4OR , vol. 13 , pp. 335–336 , 2015
    Paper DOI
  3. Composer Classification Models for Music-Theory Building
    Herremans, D. and Martens, David and Sörensen, K. and Meredith, D.
    Computational Music Analysis , 2015
    Paper DOI
  4. The effect of repetitive structure on enjoyment and altered states in uplifting trance music
    Agres, K and Bigo, L and Herremans, D and Conklin, D
    2nd International Conference on Music and Consciousness (MUSCON 2), Brighton , 2015
  5. Generating Fingerings for Polyphonic Piano Music with a Tabu Search Algorithm
    Balliauw, M. and Herremans, D. and Palhazi Cuervo, D. and Sörensen, K.
    Mathematics and Computation in Music , vol. 9110 , pp. 149-160 , 2015
    Paper DOI
  6. Generating music with an optimization algorithm using a Markov based objective function
    Herremans, D. and Weisser, S. and Sörensen, K. and Conklin, D.
    ORBEL29, Belgian Conference on Operations Research , 2015
  7. Generating structured music for bagana using quality metrics based on Markov models
    Herremans, D. and Weisser, S. and Sörensen, K. and Conklin, D.
    Expert Systems With Applications , vol. 42 (21) , pp. 424–7435 , 2015


2014

  1. Compose=Compute - Computer Generation And Classification Of Music Through Operations Research Methods
    Herremans, D.
    , pp. 250 , 2014
  2. Dance hit song prediction
    Herremans, D. and Martens, David and Sörensen, K.
    Journal of New music Research , vol. 43 , pp. 302 , 2014
    Paper
  3. First species counterpoint generation with VNS and vertical viewpoints
    Herremans, D. and Sörensen, K. and Conklin, D.
    ORBEL28 , 2014
  4. Generating structured music using quality metrics based on Markov models
    Herremans, D. and Weisser, S. and Sörensen, K. and Conklin, D.
    Technical Report, University of Antwerp (2014019) , 2014
    Paper
  5. Looking into the minds of Bach, Haydn and Beethoven: Classification and generation of composer-specific music
    Herremans, D. and Martens, David and Sörensen, K.
    Technical Report, University of Antwerp (2014001) , 2014
    Paper
  6. Markov Based Quality Metrics For Generating Structured Music With Optimization Techniques
    Herremans, D. and Weisser, S. and Sörensen, K. and Conklin, D.
    Digital Music Research Network (DMNR+9) , 2014
  7. Sampling the extrema from statistical models of music with variable neighbourhood search
    Herremans, D. and Sörensen, K. and Conklin, D.
    ICMC/SMC , 2014


2013

  1. Composing Fifth Species Counterpoint Music With A Variable Neighborhood Search Algorithm
    Herremans, D. and Sörensen, K.
    Expert Systems with Applications , vol. 40 , 2013
    Paper DOI
  2. Dance Hit Song Science
    Herremans, D. and Martens, David and Sörensen, K.
    International Workshop on Music and Machine Learning , 2013
  3. First species counterpoint generation with VNS and vertical viewpoints
    Herremans, D. and Sörensen, K. and Conklin, D.
    Digital Music Research Network (DMNR+8) , 2013
  4. FuX, an Android app that generates counterpoint
    Herremans, D. and Sörensen, K.
    IEEE Symposium on Computational Intelligence for Creativity and Affective Computing (CICAC) , pp. 48-55 , 2013
    Paper DOI


2012

  1. Composing counterpoint musical scores with variable neighborhood search
    Herremans, D. and Sörensen, K.
    ORBEL26 , 2012
  2. Composing Fifth Species Counterpoint Music With Variable Neighborhood Search
    Herremans, D. and Sörensen, K.
    Technical Report, University of Antwerp (2012020) , 2012
    Paper
  3. Composing first species counterpoint musical scores with a variable neighbourhood search algorithm
    Herremans, D. and Sörensen, K.
    Journal of Mathematics and the Arts , vol. 6 , pp. 169 - 189 , 2012
    DOI


2011

  1. A Variable Neighborhood Search Algorithm for Composing First Species Counterpoint Musical Fragments
    Herremans, D. and Sörensen, K.
    Technical Report, University of Antwerp , vol. 2011017 , 2011
    Paper


2010

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


2005

  1. Tabu Search voor de optimalisatie van muzikale fragmenten
    Herremans, D.
    , vol. MSc Business Engineer Management Information Systems , 2005