Peter Harrison, Director of the Centre for Music and Science at Churchill College and University Assistant Professor in the Faculty of Music, was recently awarded the Faculty of Music Teaching Prize, presented annually for making an outstanding contribution to the Faculty’s teaching programme.

Peter joined Churchill College in 2021. He enjoys both applied and academic aspects of music in both research and teaching, and was attracted to Churchill College because it provided a way to work in Humanities while surrounded by amazing scientists, providing the best of both worlds.  

Peter said, “What is great here is that there is really so much care for the student learning experience. I was really impressed with the College and Faculty system and people really care about making time and space for teaching.”

During the pandemic, Music teaching had to be re-set, and this provided an opportunity to experiment. Keen to ensure that students still had practical hands-on learning and to support the Music undergraduates as they prepared to move on to the next phase in their working lives, Peter instigated industry placements for summer internships working in audio branding.

This was partly in response to the challenge many Music students find in deciding what to do next, if being a professional musician is not for them. The Music and Science Centre provides a bridge to computer programming which can increase the range of options and skills undergraduate students develop, as well as ensuring that learning keeps pace with the developments and opportunities of the modern music industry.

The internships with industry partner Sound Out allowed students to get hands on with datasets of musical tracks from business partners and work to identify music which blends emotion and aesthetics to strengthen brand identity and recognition.

Peter’s research supports the quality of teaching and the creation of student opportunities like these. He specializes in computational approaches to music psychology, including cognitive modelling, massive online experiments, and corpus studies. He is particularly interested in understanding the psychological mechanisms that underlie listeners’ appreciation and enjoyment of music, and how musical styles have developed to exploit these mechanisms.

His research explores the psychological processes involved in how music stimulates emotion and enjoyment. Peter works with computational models to simulate perception and model some of these responses.

Using machine learning and artificial intelligence, the computational models draw on patterns from music, enabling identification of composers and also the ability to generate music in similar styles. Peter sees this as a useful tool to aid creativity, as in future the technology can help democratise music creation by removing barriers to access, and facilitating new compositions; for instance by helping harmonise melodies and speeding up the compositional process.

Peter’s published works cover a variety of topics, including statistical learning, creativity, musical pleasure, consonance, voice leading, harmonic syntax, and individual differences in musical abilities.