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Self-Supervised Attention Networks and Uncertainty Loss Weighting for Multi-Task Emotion Recognition on Vocal Bursts
Vincent Karas, Andreas Triantafyllopoulos, Meishu Song +1
Vocal bursts play an important role in communicating affect, making them valuable for improving speech emotion recognition. Here, we present our approach for classifying vocal burs…
Depression Diagnosis and Forecast based on Mobile Phone Sensor Data
Xiangheng He, Andreas Triantafyllopoulos, Alexander Kathan +9
Previous studies have shown the correlation between sensor data collected from mobile phones and human depression states. Compared to the traditional self-assessment questionnaires…
Fatigue Prediction in Outdoor Running Conditions using Audio Data
Andreas Triantafyllopoulos, Sandra Ottl, Alexander Gebhard +9
Although running is a common leisure activity and a core training regiment for several athletes, between and of runners sustain an overuse injury each year. These inj…
Insights on Modelling Physiological, Appraisal, and Affective Indicators of Stress using Audio Features
Andreas Triantafyllopoulos, Sandra Zänkert, Alice Baird +3
Stress is a major threat to well-being that manifests in a variety of physiological and mental symptoms. Utilising speech samples collected while the subject is undergoing an induc…
Journaling Data for Daily PHQ-2 Depression Prediction and Forecasting
Alexander Kathan, Andreas Triantafyllopoulos, Xiangheng He +9
Digital health applications are becoming increasingly important for assessing and monitoring the wellbeing of people suffering from mental health conditions like depression. A comm…
A Temporal-oriented Broadcast ResNet for COVID-19 Detection
Xin Jing, Shuo Liu, Emilia Parada-Cabaleiro +4
Detecting COVID-19 from audio signals, such as breathing and coughing, can be used as a fast and efficient pre-testing method to reduce the virus transmission. Due to the promising…