244 citations · 440 across the 15 of their papers we have counts for
15 papers
Pioneering Multimodal Emotion Recognition in the Era of Large Models: From Closed Sets to Open Vocabularies
Jing Han, Zhiqiang Gao, Shihao Gao +4
Recent advances in multimodal large language models (MLLMs) have demonstrated remarkable multi- and cross-modal integration capabilities. However, their potential for fine-grained…
Intelligent Cardiac Auscultation for Murmur Detection via Parallel-Attentive Models with Uncertainty Estimation
Zixing Zhang, Tao Pang, Jing Han +1
Heart murmurs are a common manifestation of cardiovascular diseases and can provide crucial clues to early cardiac abnormalities. While most current research methods primarily focu…
HAFFormer: A Hierarchical Attention-Free Framework for Alzheimer's Disease Detection From Spontaneous Speech
Zhongren Dong, Zixing Zhang, Weixiang Xu +3
Automatically detecting Alzheimer's Disease (AD) from spontaneous speech plays an important role in its early diagnosis. Recent approaches highly rely on the Transformer architectu…
Customising General Large Language Models for Specialised Emotion Recognition Tasks
Liyizhe Peng, Zixing Zhang, Tao Pang +4
The advent of large language models (LLMs) has gained tremendous attention over the past year. Previous studies have shown the astonishing performance of LLMs not only in other tas…
Refashioning Emotion Recognition Modelling: The Advent of Generalised Large Models
Zixing Zhang, Liyizhe Peng, Tao Pang +3
After the inception of emotion recognition or affective computing, it has increasingly become an active research topic due to its broad applications. Over the past couple of decade…
Fitbeat: COVID-19 Estimation based on Wristband Heart Rate
Shuo Liu, Jing Han, Estela Laporta Puyal +26
This study investigates the potential of deep learning methods to identify individuals with suspected COVID-19 infection using remotely collected heart-rate data. The study utilise…
CAA-Net: Conditional Atrous CNNs with Attention for Explainable Device-robust Acoustic Scene Classification
Zhao Ren, Qiuqiang Kong, Jing Han +2
Acoustic Scene Classification (ASC) aims to classify the environment in which the audio signals are recorded. Recently, Convolutional Neural Networks (CNNs) have been successfully…
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…
EmoBed: Strengthening Monomodal Emotion Recognition via Training with Crossmodal Emotion Embeddings
Jing Han, Zixing Zhang, Zhao Ren +1
Despite remarkable advances in emotion recognition, they are severely restrained from either the essentially limited property of the employed single modality, or the synchronous pr…
Snore-GANs: Improving Automatic Snore Sound Classification with Synthesized Data
Zixing Zhang, Jing Han, Kun Qian +3
One of the frontier issues that severely hamper the development of automatic snore sound classification (ASSC) associates to the lack of sufficient supervised training data. To cop…
SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild
Jean Kossaifi, Robert Walecki, Yannis Panagakis +10
Natural human-computer interaction and audio-visual human behaviour sensing systems, which would achieve robust performance in-the-wild are more needed than ever as digital devices…
Scaling Speech Enhancement in Unseen Environments with Noise Embeddings
Gil Keren, Jing Han, Björn Schuller
We address the problem of speech enhancement generalisation to unseen environments by performing two manipulations. First, we embed an additional recording from the environment alo…
Dynamic Difficulty Awareness Training for Continuous Emotion Prediction
Zixing Zhang, Jing Han, Eduardo Coutinho +1
Time-continuous emotion prediction has become an increasingly compelling task in machine learning. Considerable efforts have been made to advance the performance of these systems.…
Adversarial Training in Affective Computing and Sentiment Analysis: Recent Advances and Perspectives
Jing Han, Zixing Zhang, Nicholas Cummins +1
Over the past few years, adversarial training has become an extremely active research topic and has been successfully applied to various Artificial Intelligence (AI) domains. As a…
Learning audio sequence representations for acoustic event classification
Zixing Zhang, Ding Liu, Jing Han +2
Acoustic Event Classification (AEC) has become a significant task for machines to perceive the surrounding auditory scene. However, extracting effective representations that captur…