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Found 16 papers, 5 papers with code
The AffectToolbox: Affect Analysis for Everyone
In the field of affective computing, where research continually advances at a rapid pace, the demand for user-friendly tools has become increasingly apparent.
The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data
STOIC2021 consisted of a Qualification phase, where participants developed challenge solutions using 2000 publicly available CT scans, and a Final phase, where participants submitted their training methodologies with which solutions were trained on CT scans of 9724 subjects.
Towards Automated COVID-19 Presence and Severity Classification
COVID-19 presence classification and severity prediction via (3D) thorax computed tomography scans have become important tasks in recent times.
GANonymization: A GAN-based Face Anonymization Framework for Preserving Emotional Expressions
The effectiveness of the approach was assessed by evaluating its performance in removing identifiable facial attributes to increase the anonymity of the given individual face.
ForDigitStress: A multi-modal stress dataset employing a digital job interview scenario
We present a multi-modal stress dataset that uses digital job interviews to induce stress.
GANterfactual-RL: Understanding Reinforcement Learning Agents' Strategies through Visual Counterfactual Explanations
However, research focusing on counterfactual explanations, specifically for RL agents with visual input, is scarce and does not go beyond identifying defective agents.
An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Era
Speech is the fundamental mode of human communication, and its synthesis has long been a core priority in human-computer interaction research.
An Efficient Multitask Learning Architecture for Affective Vocal Burst Analysis
Affective speech analysis is an ongoing topic of research.
Alterfactual Explanations -- The Relevance of Irrelevance for Explaining AI Systems
We evaluate our approach in an extensive user study, revealing that it is able to significantly contribute to the participants' understanding of an AI.
"GAN I hire you?" -- A System for Personalized Virtual Job Interview Training
This feedback can be helpful concerning the improvement of behavioral skills needed for job interviews.
Alternative Data Augmentation for Industrial Monitoring using Adversarial Learning
However, a precise examination of the resulting images indicate that WGAN and image-to-image translation achieve good segmentation results and only deviate to a small degree from traditional data augmentation.
Intercategorical Label Interpolation for Emotional Face Generation with Conditional Generative Adversarial Networks
This is especially a problem if not only random new images are to be generated, but specific (continuous) features are to be co-modeled.
Dynamic Difficulty Adjustment in Virtual Reality Exergames through Experience-driven Procedural Content Generation
As a proof-of-concept, we implement an initial prototype in which the player must traverse a maze that includes several exercise rooms, whereby the generation of the maze is realized by a neural network.
Exploring emotional prototypes in a high dimensional TTS latent space
Recent TTS systems are able to generate prosodically varied and realistic speech.
GANterfactual - Counterfactual Explanations for Medical Non-Experts using Generative Adversarial Learning
By doing so, the users of counterfactual explanation systems are equipped with a completely different kind of explanatory information.
Embedded Emotions -- A Data Driven Approach to Learn Transferable Feature Representations from Raw Speech Input for Emotion Recognition
Traditional approaches to automatic emotion recognition are relying on the application of handcrafted features.
