Abstract:
At the time of writing this article, the world population is suffering from more than 2 million registered COVID-19 disease epidemic-induced deaths since the outbreak of the corona virus, which is now officially known as SARS-CoV-2. However, tremendous efforts have been made worldwide to counter-steer and control the epidemic by now labelled as pandemic. In this contribution, we provide an overview on the potential for computer audition (CA), i.e., the usage of speech and sound analysis by artificial intelligence to help in this scenario. We first survey which types of related or contextually significant phenomena can be automatically assessed from speech or sound. These include the automatic recognition and monitoring of COVID-19 directly or its symptoms such as breathing, dry, and wet coughing or sneezing sounds, speech under cold, eating behaviour, sleepiness, or pain to name but a few. Then, we consider potential use-cases for exploitation. These include risk assessment and diagnosis based on symptom histograms and their development over time, as well as monitoring of spread, social distancing and its effects, treatment and recovery, and patient well-being. We quickly guide further through challenges that need to be faced for real-life usage and limitations also in comparison with non-audio solutions. We come to the conclusion that CA appears ready for implementation of (pre-)diagnosis and monitoring tools, and more generally provides rich and significant, yet so far untapped potential in the fight against COVID-19 spread.
摘要:
在写这篇文章的时候,自冠状病毒爆发以来,世界人口正在遭受超过200万登记的COVID-19疾病流行导致的死亡,现在正式称为SARS-CoV-2。然而,全世界已经做出了巨大的努力来对抗和控制这种流行病,因为现在被标记为大流行。在这一贡献中,我们概述了计算机试听(CA)的潜力,即,在这种情况下,人工智能使用语音和声音分析来提供帮助。我们首先调查可以从语音或声音中自动评估哪些类型的相关或上下文重要的现象。这些措施包括直接自动识别和监测COVID-19或其症状,如呼吸,干,和湿咳嗽或打喷嚏的声音,冰冷的演讲,饮食行为,困倦,或痛苦的名字,但几个。然后,我们考虑潜在的用例进行开发。这些包括基于症状直方图及其随时间发展的风险评估和诊断,以及对传播的监测,社会距离及其影响,治疗和恢复,和病人的幸福。与非音频解决方案相比,我们还快速指导现实生活中需要面对的挑战和限制。我们得出的结论是,CA似乎已准备好实施(预)诊断和监控工具,更普遍的是提供丰富而重要的,但到目前为止,在对抗COVID-19传播的斗争中尚未开发的潜力。