Back to ListHuman-Centred Media Analysis
Level
Intermediate, Niche, Algorithmic, Methodological.
This topic concerns machine learning for effective computing and interaction with humans.
Learning outcomes
Content /Knowledge
Students should be able to:
- Understand the various modalities and ways by which human emotions are physically expressed.
- Understand/describe common unimodal and/or multimodal algorithms for emotion analysis, facial expression recognition, speech segmentation, speaker recognition, speech emotion recognition, text affect detection, physiological monitoring, body gesture recognition, as well as their applications in Human-Computer/Robot Interaction, computer games and education or healthcare settings.
Methodologicalskills
Students should be able to:
- Analyse and develop (in C/C++, MATLAB or Python) the taught affective computing algorithms, by practically applying their gained knowledge in a systematic manner.
- Evaluate implementations of the taught algorithms, by employing common and appropriate task-specific metrics.
Transferrable/Application
Students should be able to:
- Work effectively with others in an interdisciplinary and/or international team.
- Design and manage individual projects.
- Clearly and succinctly communicate their ideas to technical audiences.