Design and Evaluation of COVID-19 Diagnosis Software Using Voice Sound Recognition

Chang, Hao Jian (2023) Design and Evaluation of COVID-19 Diagnosis Software Using Voice Sound Recognition. Final Year Project (Bachelor), Tunku Abdul Rahman University College.

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Abstract

As COVID-19 been categories as pandemic level by the World Health Organizations (WHO) on 11 March 2020, a lot of the country have been initializing lock down in order to contain the viruses from spreading. In order to minimize the spreading of viruses, RT-PCR and RTK test is used to detect the COVID-19 in patients’ body through saliva or nasal. CT scan will be used to detect COVID-19 viruses as well as it can be found mainly in lung area. This kind of test require time and money thus it might be too late when the viruses is detected. COVID-19 diagnosis software may help in detecting the viruses in a safer and more time efficient ways as it requires only the voice of the patients as well as speech recognition technique to detect the COVID-19 viruses in the body. The use of speech recognition in this project is to help in determine the symptom of COVID- 19 by using database from COSWARA where it contain the voice sound data of COVID-19 patients as well as healthy person, several researcher has research regarding the speech recognition against the COVID-19 symptom and most of it have result obtained more than 50%. This project will discussed on several speech recognition algorithm and the working of Convolution Neural Network speech recognition. This paper will be discussed about the origin of the COVID-19 and the effects of the viruses against human and symptom of COVID-19 when contacted with it. As well as the method of detecting the symptom through speech recognition and whether it is applicable to use it during this period of time to help in reducing the spreading of COVID-19