Cough Recognition Based on Mel-Spectrogram and Convolutional Neural Network

Quan Zhou; Jianhua Shan; Wenlong Ding; Chengyin Wang; Shi Yuan; Fuchun Sun; Haiyuan Li; Bin Fang

doi:10.3389/frobt.2021.580080

Cough Recognition Based on Mel-Spectrogram and Convolutional Neural Network

Front Robot AI. 2021 May 7:8:580080. doi: 10.3389/frobt.2021.580080. eCollection 2021.

Authors

Quan Zhou¹, Jianhua Shan¹, Wenlong Ding¹, Chengyin Wang¹, Shi Yuan¹, Fuchun Sun², Haiyuan Li³, Bin Fang²

Affiliations

¹ Anhui Province Key Laboratory of Special Heavy Load Robot, Anhui University of Technology, Ma'anshan, China.
² Beijing National Research Center for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing, China.
³ Robotics Institute, School of Automation, Beijing University of Posts and Telecommunications, Beijing, China.

Abstract

In daily life, there are a variety of complex sound sources. It is important to effectively detect certain sounds in some situations. With the outbreak of COVID-19, it is necessary to distinguish the sound of coughing, to estimate suspected patients in the population. In this paper, we propose a method for cough recognition based on a Mel-spectrogram and a Convolutional Neural Network called the Cough Recognition Network (CRN), which can effectively distinguish cough sounds.

Keywords: CNN; COVID-19; audio; cough recognition; deep learning; mel-spectrogram.