关键词: 咳嗽音检测, 梅尔频率倒谱系数, 高斯混合模型, 线性组合, 小波去噪

Abstract: Rapid and precise detection of cough sound from continuous recordings is meaningful for clinical diagnosis of many respiratory diseases.This paper uses Mel-frequency cepstral coefficient as the classification feature to analyze the sound signal to be processed and creates two corresponding Gaussian mixture models for the cough sound，speech voice，laughter and throat clearing sound in the recordings respectively using multiple groups of training data，then the ultimate probability models are acquired through the means of linear combination of the two GMMs of each class.Furthermore，the theory of wavelet denoising is introduced to denoise each sound signal and then detect its endpoints.Simulation experimental results indicate that the proposed method can effectively improve the performance of the detection.

Key words: cough sound detection, Mel-frequency cepstral coefficient, Gaussian mixture model, linear combination, wavelet denoise