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Mobile application based speech and voice analysis for COVID-19 detection using computational audit techniques

Udhaya Sankar S.M. (Department of Computer Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, India)
Ganesan R. (Department of Computer Engineering, Faculty of Engineering and Technology, SRM Institute of Science and Technology, Kattankulathur, India)
Jeevaa Katiravan (Department of Information Technology, Velammal Engineering College, Chennai, India)
Ramakrishnan M. (Department of Computer Applications, Madurai Kamaraj University, Madurai, India)
Ruhin Kouser R. (Department of Computer Science and Engineering, Kingston Engineering College, Vellore, India)

International Journal of Pervasive Computing and Communications

ISSN: 1742-7371

Article publication date: 19 October 2020

Issue publication date: 25 November 2022

310

Abstract

Purpose

It has been six months from the time the first case was registered, and nations are still working on counter steering regulations. The proposed model in the paper encompasses a novel methodology to equip systems with artificial intelligence and computational audition techniques over voice recognition for detecting the symptoms. Regular and irregular speech/voice patterns are recognized using in-built tools and devices on a hand-held device. Phenomenal patterns can be contextually varied among normal and presence of asymptotic symptoms.

Design/methodology/approach

The lives of patients and healthy beings are seriously affected with various precautionary measures and social distancing. The spread of virus infection is mitigated with necessary actions by governments and nations. Resulting in increased death ratio, the novel coronavirus is certainly a serious pandemic which spreads with unhygienic practices and contact with air-borne droplets of infected patients. With minimal measures to detect the symptoms from the early onset and the rise of asymptotic outcomes, coronavirus becomes even difficult for detection and diagnosis.

Findings

A number of significant parameters are considered for the analysis, and they are dry cough, wet cough, sneezing, speech under a blocked nose or cold, sleeplessness, pain in chests, eating behaviours and other potential cases of the disease. Risk- and symptom-based measurements are imposed to deliver a symptom subsiding diagnosis plan. Monitoring and tracking down the symptoms inflicted areas, social distancing and its outcomes, treatments, planning and delivery of healthy food intake, immunity improvement measures are other areas of potential guidelines to mitigate the disease.

Originality/value

This paper also lists the challenges in actual scenarios for a solution to work satisfactorily. Emphasizing on the early detection of symptoms, this work highlights the importance of such a mechanism in the absence of medication or vaccine and demand for large-scale screening. A mobile and ubiquitous application is definitely a useful measure of alerting the officials to take necessary actions by eliminating the expensive modes of tests and medical investigations.

Keywords

Acknowledgements

Retraction notice: The publishers of International Journal of Pervasive Computing and Communications wish to retract the article “Mobile application based speech and voice analysis for COVID-19 detection using computational audit techniques” by S.M. Udhaya Sankar, R. Ganesan, J. Katiravan, M. Ramakrishnan, and R. Kouser Ruhin, which appeared ahead of print.

It has come to our attention that the data in the article is taken, without attribution, from earlier articles:

• Usman, M. (2017). On the Performance Degradation of Speaker Recognition System due to Variation in Speech Characteristics Caused by Physiological Changes. International Journal of Computing and Digital Systems. Vol. 6 (3). DOI: http://dx.doi.org/10.12785/IJCDS/060303

• Usman, M., Wajid, M., Zubair, M. and Ahmed, A. (2020). On the possibility of using Speech to detect COVID-19 symptoms: An overview and proof of concept. Preprint. DOI: 10.13140/RG.2.2.31718.57923

Despite numerous attempts to contact the authors, the journal has received no response; the response of the authors would be gratefully received.

The International Journal of Pervasive Computing and Communications submission guidelines make it clear that articles must be original and that data falsification is unacceptable. The publishers of the journal sincerely apologise to the readers and the original authors.

Citation

S.M., U.S., R., G., Katiravan, J., M., R. and R., R.K. (2022), "Mobile application based speech and voice analysis for COVID-19 detection using computational audit techniques", International Journal of Pervasive Computing and Communications, Vol. 18 No. 5, pp. 508-517. https://doi.org/10.1108/IJPCC-09-2020-0150

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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