Melechovsky J., Novotny M., Tykalova T., Klempir J., Herremans D..  2026.  Development of Interpretable Deep Learning-based Segmentation Algorithm for Automated Assessment of Oral Diadochokinesis in Progressive Neurological Diseases. Journal of Speech, Language, and Hearing Research.

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Liu R., Hung C.Y., Majumder N., Herremans D., Poria S..  2026.  JAM: A Tiny Flow-based Song Generator with Fine-grained Controllability and Aesthetic Alignment. Empirical Methods in Natural Language Processing (EMNLP).

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Lu T., Geist C-M, Melechovsky J., Roy A., Herremans D..  2026.  MelodySim: Measuring Melody-aware Music Similarity for Plagiarism Detection. IEEE Tencon.

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Melechovsky J., Mehrish A., Roy A., Herremans D..  2026.  SonicMaster: Towards Controllable All-in-One Music Restoration and Mastering. Proceedings of ICML.

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2508.03448v2.pdf (3.31 MB)

Melechovsky J., Mehrish A., Roy A., Herremans D..  2026.  SonicMaster: Towards Controllable All-in-One Music Restoration and Mastering. Proceedings of ICML.

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2508.03448v2.pdf (3.31 MB)

Melechovsky J..  2025.  Analysis and Synthesis of Audio with AI: from Neurological Disease to Accented Speech and Music.

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thesis_Jan.pdf (26.4 MB)

Tripathi A., Patle V., Jain A., Pundir A., Menon S., A. Singh K, Herremans D..  2025.  End-to-End Text-to-SQL with Dataset Selection: Leveraging LLMs for Adaptive Query Generation. Proceedings of IJCNN, Rome, Italy.

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Wei M., Modrzejewski M., Sivaraman A., Herremans D..  2025.  Prevailing Research Areas for Music AI in the Era of Foundation Models.

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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.  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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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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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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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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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)

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)

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)

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)

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)

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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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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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)

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)

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)

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)

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)

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)

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)

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)

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.

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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)

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)

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)

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)

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)

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)

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).

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2010.06230.pdf (622.82 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)

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)

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)

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., 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)

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)

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..  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)

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)