How to spot COVID-19 patients: Speech & sound audio analysis for preliminary diagnosis of SARS-COV-2 corona patients.

ABSTRACT

BACKGROUND: The global cases of COVID-19 increasing day by day. On 25 November 2020, a total of 59 850 910 cases reported globally with a 1 411 216 global death. In India, total cases in the country now stand at 91 77 841 including 86 04 955 recoveries and 4 38 667 active cases as on 24 November 2020, as per the data issued by ICMR. A new generation of voice/audio analysis application can tell whether the person is suffering from COVID-19 or not. AIMS: To describe how to established a new generation of voice/audio analysis application to identify the suspected COVID-19 hidden cases in hotspot areas with the help of an audio sample of the general public. MATERIALS & METHODS: The different patents and data available as literature on the internet are evaluated to make a new generation of voice/audio analysis application with the help of an audio sample of the general public. RESULTS: The collection of the audio sample will be done from the already suffered COVID-19 patients in (.Wave files) personally or through phone calls. The audio samples such as the sound of the cough, the pattern of breathing, respiration rate and way of speech will be recorded. The parameters will be evaluated for loudness, articulation, tempo, rhythm, melody and timbre. The analysis and interpretation of the parameters can be made through machine learning and artificial intelligence to detect corona cases with an audio sample. DISCUSSION: The voice/audio application current project can be merged with a mobile App called 'AarogyaSetu' by the Government of India. The project can be implemented in the high-risk area of COVID-19 in the country. CONCLUSION: This new method of detecting cases will decrease the workload in the COVID-19 laboratory.