University of Cambridge > Talks.cam > CMS seminar series in the Faculty of Music > Understanding music in the age of machine learning

Understanding music in the age of machine learning

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Abstract

We live in an exciting time where the abundance of digital media and advanced computational tools, such as machine learning, enables the study of music and culture on an unprecedented scale. What people listen to across different regions, communities, and historical periods offers valuable insights into understanding how human culture evolves, underlying cognitive processes and societal dynamics. In this talk, I will showcase several big-data projects that explore these themes using billions of music events across 1,423 cities captured through the web application Shazam, and tracking the music listening behaviour of over 2.5 million individuals on Deezer streaming platform. I will show how acute societal disruptions can reshape musical landscapes, the contrasts in musical diversity between urban centres and rural areas, and efforts to move beyond the traditional focus on Western music to incorporate the richness of our global musical heritage.

Biography

Harin is a PhD candidate in Cognitive Science at the Max Planck Institute in Germany, with a multidisciplinary background in sound engineering (BMus) and psychology and data sciences (MSc). His research focuses on leveraging big data to explore music from diverse cultures worldwide, complemented by large-scale cross-cultural experiments that investigate the psychological foundations of human music perception, as well as cross-cultural and individual differences. Harin is also the co-founder of ‘aiar’, an art-science collective that uses live brain imaging techniques to bring innovative approaches to music and visual art performances.

Zoom link

https://zoom.us/j/99433440421?pwd=ZWxCQXFZclRtbjNXa0s2K1Q2REVPZz09 (Meeting ID: 994 3344 0421; Passcode: 714277)

This talk is part of the CMS seminar series in the Faculty of Music series.

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