Abstract
Background: The global cases of Covid-19 increasing day by day.
On Nov. 25, 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 Nov. 24, 2020, as per the data issued by ICMR. A new generation of
voice/audio analysis application which 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 like 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 Govt. 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.
Keywords: Machine learning, Artificial intelligence, Covid-19,
Corona, Audio/voice