Audio, Speech, Language, & Signal Processing for COVID-19: A Comprehensive Overview
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.
Cite
@article{arxiv.2011.14445,
title = {Audio, Speech, Language, & Signal Processing for COVID-19: A Comprehensive Overview},
author = {Gauri Deshpande and Björn W. Schuller},
journal= {arXiv preprint arXiv:2011.14445},
year = {2020}
}
Comments
arXiv admin note: text overlap with arXiv:2005.08579