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 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 of
Nov. 24, 2020, as per 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 establish a new
generation of voice/audio analysis applications 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 “Aarogya Setu”
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.