For more publications, see my Google scholar profile.
Huang, C.A., Koops, H.V., Newton-Rex, E., Dinculescu, M., Cai, C. (2020). Human-AI Co-Creation in Songwriting. Accepted for publication in Proceedings of the 19th International Society for Music Information Retrieval Conference.
Odekerken, D., Koops, H.V., & Volk, A. (2020). DECIBEL: Improving Audio Chord Estimation for Popular Music by Alignment and Integration of Crowd-Sourced Symbolic Representations. arXiv preprint arXiv:2002.09748.
Selway, A., Koops, H.V., Volk, A., Bretherton, D., Gibbins, N., & Polfreman, R. (2020). Explaining harmonic inter-annotator disagreement using Hugo Riemann’s theory of ‘harmonic function’. Journal of New Music Research, 49(2), 136–150.
Koops, H.V. (2019). Computational modelling of variance in musical harmony. (Doctoral dissertation, Utrecht University).
Koops, H.V., Haas, W., Burgoyne, J., Bransen, J., Kent-Muller, A., & Volk, A. (2019). Annotator subjectivity in harmony annotations of popular music. Journal of New Music Research, 48(3), 232–252.
Ren, Y., Nieto, O., Koops, H.V., Volk, A., & Swierstra, W. (2018). Investigating Musical Pattern Ambiguity in a Human Annotated Dataset. Utrecht University Repository
Koops, H.V., Haas, W.B., Bransen, J., & Volk, A. (2018). Automatic chord label personalization through deep learning of shared harmonic interval profiles. Neural Computing and Applications, 1–11.
Schotanus, Y., Koops, H. V., & Reed Edworthy, J. (2018). Interaction between musical and poetic form affects song popularity: The case of the Genevan Psalter. Psychomusicology: Music, Mind, and Brain, 28(3), 127–151.
Ren, I., Koops, H.V., Bountouridis, D., Volk, A., Swierstra, W., & Veltkamp, R. (2018). Feature Analysis Of Repeated Patterns In Dutch Folk Songs Using Principal Component Analysis. In Proceedings of Folk Music Analysis 2018.
Koops, H.V., Garg, K., Kim M, L., A., V., & F., F. (2017). Multirotor UAV State Prediction Through Multi-Microphone Side-Channel Fusion. In 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (pp. 15–21).
Koops, H.V., Haas, W., Burgoyne, J., Bransen, J., & Volk, A.. (2017). Harmonic subjectivity in popular music.
Koops, H.V., Haas, W., Bransen, J., Burgoyne, J., & Volk, A. (2017). Chordify Annotator Subjectivity Dataset. In Late Breaking/Demo Sessions at the 18th International Society for Music Information Retrieval Conference.
Odekerken, D., Volk, A., & Koops, H.V. (2017). Rhythmic Patterns in Ragtime and Jazz. In Proceedings of the 7th International Workshop on Folk Music Analysis (pp. 44–49).
Ren, I., Koops, H.V., Volk, A., & Swierstra, W. (2017). In Search Of The Consensus Among Musical Pattern Discovery Algorithms. In Proceedings of the 18th International Society for Music Information Retrieval Conference.
Koops, H.V., Haas, W., Bransen, J., & Volk, A. (2017). Chord Label Personalization through Deep Learning of Integrated Harmonic Interval-based Representations. In Proceedings of the First International Workshop on Deep Learning and Music (pp. 19–25).
Bountouridis, D., Brown, D., Koops, H.V., Wiering, F., & Veltkamp, R. (2017). Melody retrieval and classification using biologically-inspired techniques. In International Conference on Evolutionary and Biologically Inspired Music and Art (pp. 49–64).
Koops, H.V., Garg, K., Kim, M., Li, J., Volk, A., & Franchetti, F.. (2017). Prediction of Quadcopter State through Multi-Microphone Side-Channel Fusion.
Bountouridis, D., Koops, H.V., Wiering, F., & Veltkamp, R. (2016). Music outlier detection using multiple sequence alignment and independent ensembles. In International Conference on Similarity Search and Applications (pp. 286–300).
Koops, H.V., Haas, W., Bountouridis, D., & Volk, A. (2016). Integration and quality assessment of heterogeneous chord sequences using data fusion. In International Society for Music Information Retrieval Conference (pp. 178–184).
Bountouridis, D., Koops, H.V., Wiering, F., & Veltkamp, R. (2016). A data-driven approach to chord similarity and chord mutability. In 2016 IEEE Second International Conference on Multimedia Big Data (BigMM) (pp. 275–278).
Koops, H.V., Volk, A., & De Haas, W.B. (2015). Corpus-based rhythmic pattern analysis of ragtime syncopation. In Proceedings of the 16th International Society for Music Information Retrieval Conference, ISMIR 2015 (pp. 483–489).
Koops, H.V., Haas, W., & Volk, A. (2015). Integration of Crowd-Sourced Chord Sequences Using Data Fusion. In 16th International Society for Music Information Retrieval Conference.
Koops, H.V., & Franchetti, F. (2015). An Ensemble Technique for Estimating Vehicle Speed and Gear Position from Acoustic Data. In Digital Signal Processing (DSP), 2015 IEEE International Conference on (pp. 422–426).
Koops, H.V., Van Balen, J., & Wiering, F. (2015). Automatic segmentation and deep learning of bird sounds. In International Conference of the Cross-Language Evaluation Forum for European Languages (pp. 261–267).
Koops, H.V., Van Balen, J., & Wiering, F. (2014). A Deep Neural Network Approach to the LifeCLEF 2014 Bird TaskCLEF2014 Working Notes, 1180, 634–642.
Koops, H.V. (2014). A Deep Neural Network Approach to Automatic Birdsong Recognition. (Doctoral dissertation, Utrecht University).
Magalhães, J.P., & Koops, H.V. (2014). Functional generation of harmony and melody. In Proceedings of the 2nd ACM SIGPLAN international workshop on Functional art, music, modeling & design (pp. 11–21).
Koops, H.V. (2012). A Model Based Approach to Automatic Harmonization of a Melody. (Doctoral dissertation, Utrecht University).
Koops, H.V., Magalhães, J.P., & De Haas, W.B. (2013). A Functional Approach to Automatic Melody Harmonisation. In Proceedings of the first ACM SIGPLAN workshop on Functional art, music, modeling & design (pp. 47–58).