Can a machine really learn about and infer emotions from digitised behaviour?
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Affective computing refers to the use of computers to analyse data about human behaviour, such as facial expressions, gestures, and language, for its emotional information.
But can a machine really learn about and infer emotions from digitised behaviour, typically captured as text, images, audio and video? How does it compare with human performance? How well do we understand how emotions are expressed and why? In this talk, we will look at the theories and the algorithms, and the benefits and consequences of their application in real-world situations.
About the speaker
Sharon Richardson, PhD, is a senior scientist in geocomputation at the University of Zürich. Her research focuses on investigating and applying data-intensive methods to improve understanding of and assist in human, societal and environmental challenges.