83 citations · 118 across the 10 of their papers we have counts for
10 papers
MADUV: The 1st INTERSPEECH Mice Autism Detection via Ultrasound Vocalization Challenge
Zijiang Yang, Meishu Song, Xin Jing +7
The Mice Autism Detection via Ultrasound Vocalization (MADUV) Challenge introduces the first INTERSPEECH challenge focused on detecting autism spectrum disorder (ASD) in mice throu…
U-DiT TTS: U-Diffusion Vision Transformer for Text-to-Speech
Xin Jing, Yi Chang, Zijiang Yang +3
Deep learning has led to considerable advances in text-to-speech synthesis. Most recently, the adoption of Score-based Generative Models (SGMs), also known as Diffusion Probabilist…
HEAR4Health: A blueprint for making computer audition a staple of modern healthcare
Andreas Triantafyllopoulos, Alexander Kathan, Alice Baird +20
Recent years have seen a rapid increase in digital medicine research in an attempt to transform traditional healthcare systems to their modern, intelligent, and versatile equivalen…
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…
An Early Study on Intelligent Analysis of Speech under COVID-19: Severity, Sleep Quality, Fatigue, and Anxiety
Jing Han, Kun Qian, Meishu Song +11
The COVID-19 outbreak was announced as a global pandemic by the World Health Organisation in March 2020 and has affected a growing number of people in the past few weeks. In this c…