AI-Based human audio processing for COVID-19: A comprehensive overview. (February 2022)

• Record Type: Journal Article
• Authors: Deshpande, Gauri; Batliner, Anton; Schuller, Björn W.
• Is Part Of: Pattern recognition. Volume 122(2022)
• Publication Date: 2022-02
• Subjects: COVID-19 -- Digital health -- Audio processing -- Computational paralinguistics; Pattern perception -- Periodicals; Perception des structures -- Périodiques; Patroonherkenning; 006.4
• DOI: 10.1016/j.patcog.2021.108289
• Languages: English
• ISSNs: 0031-3203

Abstract

Highlights: Survey of audio processing techniques for COVID-19 related health problems. COVID-19 screening, and diagnosing using audio-based analysis. Artificial intelligence techniques used for detecting COVID-19 from audio signals. Abstract: The Coronavirus (COVID-19) pandemic impelled several research efforts, from collecting COVID-19 patients' data to screening them for virus detection. Some COVID-19 symptoms are related to the functioning of the respiratory system that influences speech production; this suggests research on identifying markers of COVID-19 in speech and other human generated audio signals. In this article, we give an overview of research on human audio signals using 'Artificial Intelligence' techniques to screen, diagnose, monitor, and spread the awareness about COVID-19. This overview will be useful for developing automated systems that can help in the context of COVID-19, using non-obtrusive and easy to use bio-signals conveyed in human non-speech and speech audio productions.