64 citations · 109 across the 7 of their papers we have counts for
7 papers
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…
Recent Advances in Computer Audition for Diagnosing COVID-19: An Overview
Kun Qian, Bjorn W. Schuller, Yoshiharu Yamamoto
Computer audition (CA) has been demonstrated to be efficient in healthcare domains for speech-affecting disorders (e.g., autism spectrum, depression, or Parkinson's disease) and bo…
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…
deepSELF: An Open Source Deep Self End-to-End Learning Framework
Tomoya Koike, Kun Qian, Björn W. Schuller +1
We introduce an open-source toolkit, i.e., the deep Self End-to-end Learning Framework (deepSELF), as a toolkit of deep self end-to-end learning framework for multi-modal signals.…
COVID-19 and Computer Audition: An Overview on What Speech & Sound Analysis Could Contribute in the SARS-CoV-2 Corona Crisis
Björn W. Schuller, Dagmar M. Schuller, Kun Qian +3
At the time of writing, the world population is suffering from more than 10,000 registered COVID-19 disease epidemic induced deaths since the outbreak of the Corona virus more than…
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…
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…