Audio, Speech, Language, & Signal Processing for COVID-19: A Comprehensive Overview
This paper is an incremental overview for researchers and developers working on automated, non-obtrusive COVID-19 detection and monitoring systems using audio-based modalities.
This paper provides a comprehensive overview of research utilizing audio, speech, language, and general signal processing techniques with AI for COVID-19 screening, diagnosis, monitoring, and awareness. It covers efforts from data collection to symptom detection, highlighting the connection between respiratory symptoms and speech production.
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.