47 citations · 117 across the 15 of their papers we have counts for
10 papers · 1 filter
STAA-Net: A Sparse and Transferable Adversarial Attack for Speech Emotion Recognition
Yi Chang, Zhao Ren, Zixing Zhang +6
Speech contains rich information on the emotions of humans, and Speech Emotion Recognition (SER) has been an important topic in the area of human-computer interaction. The robustne…
A Comprehensive Survey on Heart Sound Analysis in the Deep Learning Era
Zhao Ren, Yi Chang, Thanh Tam Nguyen +3
Heart sound auscultation has been applied in clinical usage for early screening of cardiovascular diseases. Due to the high demand for auscultation expertise, automatic auscultatio…
Fast Yet Effective Speech Emotion Recognition with Self-distillation
Zhao Ren, Thanh Tam Nguyen, Yi Chang +1
Speech emotion recognition (SER) is the task of recognising human's emotional states from speech. SER is extremely prevalent in helping dialogue systems to truly understand our emo…
Knowledge Transfer For On-Device Speech Emotion Recognition with Neural Structured Learning
Yi Chang, Zhao Ren, Thanh Tam Nguyen +2
Speech emotion recognition (SER) has been a popular research topic in human-computer interaction (HCI). As edge devices are rapidly springing up, applying SER to edge devices is pr…
Example-based Explanations with Adversarial Attacks for Respiratory Sound Analysis
Yi Chang, Zhao Ren, Thanh Tam Nguyen +2
Respiratory sound classification is an important tool for remote screening of respiratory-related diseases such as pneumonia, asthma, and COVID-19. To facilitate the interpretabili…
Robust Federated Learning Against Adversarial Attacks for Speech Emotion Recognition
Yi Chang, Sofiane Laridi, Zhao Ren +3
Due to the development of machine learning and speech processing, speech emotion recognition has been a popular research topic in recent years. However, the speech data cannot be p…
Prototype Learning for Interpretable Respiratory Sound Analysis
Zhao Ren, Thanh Tam Nguyen, Wolfgang Nejdl
Remote screening of respiratory diseases has been widely studied as a non-invasive and early instrument for diagnosis purposes, especially in the pandemic. The respiratory sound cl…
The EIHW-GLAM Deep Attentive Multi-model Fusion System for Cough-based COVID-19 Recognition in the DiCOVA 2021 Challenge
Zhao Ren, Yi Chang, Björn W. Schuller
Aiming to automatically detect COVID-19 from cough sounds, we propose a deep attentive multi-model fusion system evaluated on the Track-1 dataset of the DiCOVA 2021 challenge. Thre…
Deep Attention-based Representation Learning for Heart Sound Classification
Zhao Ren, Kun Qian, Fengquan Dong +3
Cardiovascular diseases are the leading cause of deaths and severely threaten human health in daily life. On the one hand, there have been dramatically increasing demands from both…
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…