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.

• Google Scholar
• BibTeX

concert_paper_preprint.pdf (1.6 MB)

Angus 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.

• Google Scholar
• BibTeX

angus_jaes_preprint.pdf (6.39 MB)

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.

• Google Scholar
• BibTeX

preprint_lstm.pdf (741.28 KB)

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

• Google Scholar
• BibTeX

herremans2017work2vec.pdf (745.8 KB)

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

• Google Scholar
• BibTeX

herremans2017morpheusFullIEEE.pdf (5.71 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.

• Google Scholar
• BibTeX

paper_preprint.pdf (1.63 MB)

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) .

• Google Scholar
• BibTeX

agres_herr_music_rehab_preprint.pdf (1.77 MB)

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

• Google Scholar
• BibTeX

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.

• Google Scholar
• BibTeX

abstract_dagstuhl_dh.pdf (88.49 KB)

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.

• Google Scholar
• BibTeX

orbel30_dh.pdf (117.78 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).

• Google Scholar
• BibTeX

dmrn9_dh.pdf (133.29 KB)