Master theses

  • Marc Ferrigi (2023), Improving the Player Experience of Collaborative Multiplayer Games for Visually Impaired Children.
  • Robin Ungruh (2023), Mitigating Popularity Bias in Music Recommender Systems. Effects on Fair Exposure, User Perception, and Motivation for Exploration.
  • Ermis Chalkiadakis (2022), Developing and evaluating a Musical Attention Control Training computer game application.
  • Evangelos Potamianos (2022), Designing an inclusive multiplayer rhythm game for visually impaired and sighted children.
  • Amalia Musters (2022), Assessing Sensory Processing Deficits of Children with Autism Spectrum Disorder Using a Rhythmic Game: Quantifying Performance on Rhythm Tasks.
  • Diego Ligtenberg (2022), The Effect of Deep Learning-based Source Separation on Predominant Instrument Classification in Polyphonic Music. 
  • Thomas Fink (2022), Sonification - Extending the Visual Arts experience.
  • Thomas Dallmeir (2022), Difference in User Types for User-Generated Playlist Creation on Music Streaming Platforms.
  • Evangelos Potamianos (2022), Designing an inclusive multiplayer rhythm game for visually impaired and sighted children.
  • Niek de Gier (2022), Detecting Musical Rhetoric Figures with LSTM using Procedurally Generated Synthetic Data.
  • Bart Broekman (2021), Establishing an evaluator for musical features and video game segments.
  • Alysha Bogaers (2020), Music-Driven Generation of Expressive Musical Gestures.
  • Cas Laugs (2020), Creating a Speech- and Music Emotion Recognition System for Mixed Source Audio.
  • Jerry Hu (2020), Automatic melody composition with Evolutionary Algorithms.
  • Stephan Wells (2019), Creating a Tool for Facilitating and Researching Human Annotation of Musical Patterns.
  • Arianne Nieuwenhuizen (2019): Music Thumbnailing by Hooks. 
  • Eric Scerri (2019), An Approach for Automated Pattern Discovery in Symbolic Music with Long Short-Term Memory Neural Networks.
  • Koen Schalkwijk (2019), Improving Sound Event Detection Using Neural Network Trees.
  • Daphne Odekerken (2018), Audio-Symbolic Alignment of Popular Music with Application to Automatic Chord Recognition.
  • Peter Boot (2015), Using discovered and annotated patterns for determining similarity between folk songs.
  • Jeroen Witteveen (2014), Predicting Relevance of Emotion Tags.Jan de Wit (2012): Multiple fundamental frequency estimation and instrument recognition using non-negative matrix factorization.
  • Justin de Nooijer (2007), Cognition-based Segmentation for Music Information Retrieval Systems.
  • Selma Noordergraaf (2016), Melodic cadences in Dutch monophonic songs.