Recent advances in computer audition for diagnosing Covid-19: An overview

Kun Qian*, Björn W. Schuller, Yoshiharu Yamamoto*

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

10 引用 (Scopus)

摘要

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 body sound-affecting abnormalities (e. g., abnormal bowel sounds, heart murmurs, or snore sounds). Nevertheless, CA has been underestimated in the considered data-driven technologies for fighting the COVID-19 pandemic caused by the SARS-CoV-2 coronavirus. In this light, summarise the most recent advances in CA for COVID-19 speech and/or sound analysis. While the milestones achieved are encouraging, there are yet not any solid conclusions that can be made. This comes mostly, as data is still sparse, often not sufficiently validated and lacking in systematic comparison with related diseases that affect the respiratory system. In particular, CA-based methods cannot be a standalone screening tool for SARS-CoV-2. We hope this brief overview can provide a good guidance and attract more attention from a broader artificial intelligence community.

源语言英语
主期刊名LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies
出版商Institute of Electrical and Electronics Engineers Inc.
181-182
页数2
ISBN(电子版)9781665418751
DOI
出版状态已出版 - 9 3月 2021
已对外发布
活动3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021 - Nara, 日本
期限: 9 3月 202111 3月 2021

出版系列

姓名LifeTech 2021 - 2021 IEEE 3rd Global Conference on Life Sciences and Technologies

会议

会议3rd IEEE Global Conference on Life Sciences and Technologies, LifeTech 2021
国家/地区日本
Nara
时期9/03/2111/03/21

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