Course: Mood Technology for Creative Practice

In Spring 2017, I have designed and offered a new course at UC Irvine, in the School of the Arts, at the Department of Dance: “Mood Technology for Creative Practice”. The course will be available again to all UCI students, this coming fall.

The following is an extract from the Syllabus of the course.

The course is an interdisciplinary introduction to media technology of next generation that can interact in terms of moods, with a specific focus on interactive music systems, motion capture technology and dance, taught by Dr. Fabio Paolizzo.

This course will provide the opportunity to work with and learn from Dr. Paolizzo, visiting scholar and principal investigator of the Musical-Moods project. The project is aimed at the development of an online database of music scores, music lyrics, audio excerpts, vector-based 3D animations and dance video recordings, indexed by mood for next generation of media technology. The course covers the basic principles and implications of bridging the creative and the technical in contemporary society. The Musical-Moods project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 659434.

Upper-level undergraduate and graduate students in Music or Dance will get out of the course a solid understanding of existing and emerging approaches to innovative creative practices leveraging on state of the art technology. Students will have freedom of choice in focusing on the technological aspects of the project or participating as dancers and be featured with the project.

Students will foster knowledge and skills to experiment successfully with improvisation of dance and music, analyze creative performances, acquire experience with dance and music for motion capture technology, as well as inspire new approaches to machine learning in real world scenarios.

The course is focused on hands-on collaborative research activities and/or creative practice. No advanced knowledge of technology is expected.

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