Music Information Computing
Music Information Computing lies at the intersection of computer and information sciences, mathematics, and music. We decipher through computational modelling the information processing in music that complements information processing in other domains such as language and vision, enabling research on music as a fundamental human trait and and facilitating new ways of interaction with music.
Our research has contributed to establishing research on music information computing on an international level, in areas such as Music Information Retrieval (MIR); Computational Musicology; Mathematical Music Theory; Music Cognition and Music, Computing and Health.
Our research areas include:
- Computational models for rhythm and meter, melody, harmony, patterns and segments
- Music similarity, classification and retrieval
- Computational annotation tools for studying subjective experiences of music
- Music emotion recognition, musical salience and hooks
- Gamified musical interactions
- Corpus-based computational studies of music
- Artificial intelligence for music analysis and generation
- Fairness and bias mitigation in music recommender systems
- Music technology for health and well-being
- Inclusive music-based games
- Linked data structures for musical heritage
We collaborate across the department involving Artificial Intelligence, Data Science, Human Centered Computing, Software Technology, Multimedia, Social and Affective Computing, and contribute to university-wide topics such as Dynamics of Youth, Digital Humanities, and Game research.