Music, Emotion & Cognition
I have a long standing interest on the study of the emotional impact of music on listeners.
In particular, I am interested in
- the link between music structure and emotion,
- the types of emotions induced by music,
- the individual and contextual factors that mediate the relationships between music and listeners
- the impact of music in everyday life activities (e.g., exercising, studying, driving, ...)
- the automatic recognition of emotion in music and voice.
Music in Healthcare / Healthcare Informatics
One of my main research interests is the application of music in Healthcare (e.g., stroke recovery, treatment of depression) and Eldercare.
In relation to Healthcare, my central aim is to develop a better understanding about the use of music to cope with health challenges (e.g., depression, stroke recovery) and the creation of tools that can empower people to deal with these challenges autonomously. As an example, my current focus is the creation of music recommendation systems for the treatment of Depression Disorders.
In relation to Eldercare, my focus in on improving the well-being and quality of life of dementia patients and their caregivers through music. My main interest is to explore the mechanisms underlying the
positive effects of music on the overall well-being of dementia sufferers as well as the indirect effects on quality of life of their caregivers/family members. In this context, my focus is on on individual meaningful music listening and the exploration of the elicitation of autobiographical memories to help dementia sufferers to recall life experiences and regenerate the sense of empowerment.
Music Technology and Interactive Arts
I have a long standing interest in Sound ecology, Automatic Music Composition, Sound Design, Hybrid music systems and Interactive environments. Often I engage in both research and artistic projects in these areas.
Professor Björn Schuller
Project: Computational Paralinguistics
External: University of Passau (Germany) and Imperial College London (UK)
Automatic analysis and identification of speakers states and traits from the voice with applications to human computer interaction, psychology research and healthcare.
Professor Nicola Dibben
Project: Expression and perception of Emotion in Music and Speech
External: University of Sheffield
- Identification of similarities between the acoustic patterns communication emotion to listeners in music and speech.
- Analysis of the links between physiological patterns and perception of emotion in music and speech.
- Individual differences in the perception of emotion in music and speech
Professor Klaus Scherer
Project: Musical emotions: nature, factors and determinants
External: Swiss Center for Affective Sciences
- Identification of the types of emotion induced by music
- Identification of the factors influencing the induction of emotion through music