Abstract
AbstractThe objective of this research is to recognize the speech signals for identifying the Covid-19 using K Nearest Neighbour (KNN) and comparing accuracy with an Artificial Neural Network (ANN). Speech recognition using KNN is considered as group 1 and Artificial Neural Network is considered as group 2, where each group has 20 samples. ANN is a machine learning program in which the input is processed by numerous elements and produces the output based on predefined functions. KNN is defined to find the relations between the query and pick the value closest to the query. These groups were analyzed by an independent sample T-test with 5% of alpha, and 80% of pretest power. ANN and KNN achieve an accuracy of 83.5% and 91.49% respectively (significance < 0.05). This analysis observed that KNN has significantly higher accuracy than ANN.KeywordsMachine learningInnovative speech recognitionCovid-19 detectionK nearest neighbourArtificial neural networkStatistical analysis
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