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Enhancing Emotional Text-to-Speech Controllability with Natural Language Guidance through Contrastive Learning and Diffusion Models
Xin Jing, Kun Zhou, Andreas Triantafyllopoulos +1
While current emotional text-to-speech (TTS) systems can generate highly intelligible emotional speech, achieving fine control over emotion rendering of the output speech still rem…
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…
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…
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…
An Overview & Analysis of Sequence-to-Sequence Emotional Voice Conversion
Zijiang Yang, Xin Jing, Andreas Triantafyllopoulos +3
Emotional voice conversion (EVC) focuses on converting a speech utterance from a source to a target emotion; it can thus be a key enabling technology for human-computer interaction…