Audio, Speech, Language, & Signal Processing for COVID-19: A Comprehensive Overview

TL;DR

This paper reviews AI-based audio and speech processing methods used for COVID-19 detection, diagnosis, and monitoring, emphasizing non-intrusive, speech-based screening tools developed during the pandemic.

Contribution

It provides a comprehensive overview of existing research on speech and audio signal processing for COVID-19, highlighting new AI-driven approaches and potential for automated screening.

Findings

AI techniques identify COVID-19 markers in speech and audio signals

Speech-based systems can assist in non-invasive COVID-19 screening

Research shows promising results for audio-based COVID-19 detection

Abstract

The Coronavirus (COVID-19) pandemic has been the research focus world-wide in the year 2020. Several efforts, from collection of COVID-19 patients' data to screening them for the virus's detection are taken with rigour. A major portion of COVID-19 symptoms are related to the functioning of the respiratory system, which in-turn critically influences the human speech production system. This drives the research focus towards identifying the markers of COVID-19 in speech and other human generated audio signals. In this paper, we give an overview of the speech and other audio signal, language and general signal processing-based work done using Artificial Intelligence techniques to screen, diagnose, monitor, and spread the awareness aboutCOVID-19. We also briefly describe the research related to detect accord-ing COVID-19 symptoms carried out so far. We aspire that this collective information will be useful in developing automated systems, which can help in the context of COVID-19 using non-obtrusive and easy to use modalities such as audio, speech, and language.