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

Abstract

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.

arXiv comment5 pages

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Cited by in corpus (8)

• Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data
• COVID-19 Cough Classification using Machine Learning and Global Smartphone Recordings
• Cough Against COVID: Evidence of COVID-19 Signature in Cough Sounds
• Interpreting glottal flow dynamics for detecting COVID-19 from voice
• Detecting COVID-19 from Breathing and Coughing Sounds using Deep Neural Networks
• Pay Attention to the cough: Early Diagnosis of COVID-19 using Interpretable Symptoms Embeddings with Cough Sound Signal Processing
• Studying the Similarity of COVID-19 Sounds based on Correlation Analysis of MFCC
• Impact of data-splits on generalization: Identifying COVID-19 from cough and context