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Seminar: Machine Learning for Emotion Recognition  SS2024

News

  • Kick off meeting on 25.04.2024.

Description

For machines to interact with humans in a natural way, they need to understand the emotional state of humans. Recognizing emotional states is challenging due to the large variability and often subtle nature of emotion expressions. The focus of this seminar is on improving the performance of emotion recognition approaches with modern machine learning algorithms. Students will work in small teams on well-defined practical projects in the field of emotion recognition. The possible projects include video-based emotion recognition from people’s body movements, speech, as well as from Electroencephalography (EEG) recordings. The seminar will allow students to get hands-on experience in applied machine learning. 

After three initial meetings in the full group, each team will be closely supervised by the seminar organisers. The deliverables include intermediate and end-of-term presentations, as well as a concise written report. 

Number of Participants: 6-12 students

Requirements

  • The seminar is targeted at master students interested in pursuing research in the social signal processing and affective computing domains;
  • Theoretical and practical knowledge in machine learning, especially deep learning.;
  • Practical experience with scientific computing in Python.

Organisers: Philipp Müller, Mina Ameli, Benedikt Emanuel Wirth.
This seminar is held at DFKI

LSF page: TBD

Organisational information

The seminar will be in Barwise room, DFKI D3.4

The room is located beside the reception, in the entry level.
(You are very welcome to ask at the front desk for instructions on getting there)

Thursdays between 14:00 and 16:00

 

Material

TBD