Causes for the diversity of affective reactions to music
are extremely difficult to trace. To maximize results, the
focus of the Affective Listener is
on a clearly
defined subset of music perception (see mapping).
Through observation and analysis of
trends within this
microcosm,
we hope to gain insight into the relation between specific parameters
of music and their abilities to induce affective change.
The challenge lies in the correlation of specific parameters
of music to specific changes
in affective state:
Project overview:
Small-scale listening experiment:
Change music parameters, and observe changes in physiological and self-report
data.
Music generator:
Develop real-time algorithm that modifies music parameters based on affect.
Issues:
• Devise mapping scheme of music parameters
• Correlate affective signals with music parameters
• Disambiguate data collected during music listening
• Develop algorithm to navigate music map by affect
