Deep-learning models of NTUA-SLP team submitted in SemEval 2018 tasks 1, 2 and 3.
-
Updated
Jun 21, 2022 - Python
Deep-learning models of NTUA-SLP team submitted in SemEval 2018 tasks 1, 2 and 3.
Code for Stress and Affect Detection on Resource-Constrained Devices
This repository contains the code, dataset, and model outputs for the ICMI 2024 paper Multimodal User Enjoyment Detection in Human-Robot Conversation: The Power of Large Language Models. It includes scripts for prompting LLMs, training supervised models, and evaluating multimodal enjoyment detection.
Add a description, image, and links to the affect-recognition topic page so that developers can more easily learn about it.
To associate your repository with the affect-recognition topic, visit your repo's landing page and select "manage topics."