# An Overview on Audio, Signal, Speech, & Language Processing for COVID-19

arXiv: https://arxiv.org/abs/2005.08579 · HTML: https://mlsanity.com/paper/2005.08579/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 May 2020.

## Built on by (most cited first, 5 of 5)

- [Virufy: A Multi-Branch Deep Learning Network for Automated Detection of COVID-19](https://mlsanity.com/paper/2103.01806/) (2021)
- [WavRx: a Disease-Agnostic, Generalizable, and Privacy-Preserving Speech Health Diagnostic Model](https://mlsanity.com/paper/2406.18731/) (2024)
- [Automatic COVID-19 disease diagnosis using 1D convolutional neural network and augmentation with human respiratory sound based on parameters: cough, breath, and voice](https://mlsanity.com/paper/2112.07285/) (2021)
- [Tuberculosis Screening from Cough Audio: Baseline Models, Clinical Variables, and Uncertainty Quantification](https://mlsanity.com/paper/2601.07969/) (2026)
- [Impact of data-splits on generalization: Identifying COVID-19 from cough and context](https://mlsanity.com/paper/2106.03851/) (2021)

## Abstract (arXiv)

Recently, there has been an increased attention towards innovating, enhancing, building, and deploying applications of speech signal processing for providing assistance and relief to human mankind from the Coronavirus (COVID-19) pandemic. Many AI with speech initiatives are taken to combat with the present situation and also to create a safe and secure environment for the future. This paper summarises all these efforts taken by the re-search community towards helping the individuals and the society in the fight against COVID-19 over the past 3-4 months using speech signal processing. We also summarise the deep techniques used in this direction to come up with capable solutions in a short span of time. This paper further gives an overview of the contributions from non-speech modalities that may complement or serve as inspiration for audio and speech analysis. In addition, we discuss our observations with respect to solution usability, challenges, and the significant technology achievements.