83 citations · 118 across the 10 of their papers we have counts for
6 papers · 1 filter
An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Era
Andreas Triantafyllopoulos, Björn W. Schuller, Gökçe İymen +9
Speech is the fundamental mode of human communication, and its synthesis has long been a core priority in human-computer interaction research. In recent years, machines have manage…
Redundancy Reduction Twins Network: A Training framework for Multi-output Emotion Regression
Xin Jing, Meishu Song, Andreas Triantafyllopoulos +2
In this paper, we propose the Redundancy Reduction Twins Network (RRTN), a redundancy reduction training framework that minimizes redundancy by measuring the cross-correlation matr…
Dynamic Restrained Uncertainty Weighting Loss for Multitask Learning of Vocal Expression
Meishu Song, Zijiang Yang, Andreas Triantafyllopoulos +6
We propose a novel Dynamic Restrained Uncertainty Weighting Loss to experimentally handle the problem of balancing the contributions of multiple tasks on the ICML ExVo 2022 Challen…
Exploring speaker enrolment for few-shot personalisation in emotional vocalisation prediction
Andreas Triantafyllopoulos, Meishu Song, Zijiang Yang +2
In this work, we explore a novel few-shot personalisation architecture for emotional vocalisation prediction. The core contribution is an `enrolment' encoder which utilises two unl…
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…