IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
Vol 16, No 3 (2022): July

Spectrogram Window Comparison: Cough Sound Recognition using Convolutional Neural Network

Dzikri Rahadian Fudholi (Department of Computer Science and Electronics, FMIPA UGM, Yogyakarta)
Muhammad Auzan (Department of Computer Science and Electronics, FMIPA UGM, Yogyakarta)
Novia Arum Sari (Department of Computer Science and Electronics, FMIPA UGM, Yogyakarta)



Article Info

Publish Date
31 Jul 2022

Abstract

 Cough is one of the most common symptoms of diseases, especially respiratory diseases. Quick cough detection can be the key to the current pandemic of COVID-19. Good cough recognition is the one that uses non-intrusive tools such as a mobile phone microphone that does not disable human activities like stick sensors. To do sound-only detection, Deep Learning current best method Convolutional Neural Network (CNN) is used. However, CNN needs image input while sound input differs (one dimension rather than two). An extra process is needed, converting sound data to image data using a spectrogram. When building a spectrogram, there is a question about the best size. This research will compare the spectrogram's size, called Spectrogram Window, by the performance. The result is that windows with 4 seconds have the highest F1-score performance at 92.9%. Therefore, a window of around 4 seconds will perform better for sound recognition problems.

Copyrights © 2022






Journal Info

Abbrev

ijccs

Publisher

Subject

Computer Science & IT Control & Systems Engineering

Description

Indonesian Journal of Computing and Cybernetics Systems (IJCCS), a two times annually provides a forum for the full range of scholarly study . IJCCS focuses on advanced computational intelligence, including the synergetic integration of neural networks, fuzzy logic and eveolutionary computation, so ...