计算机工程与应用2011，Vol.47Issue(32)：151-154,4.DOI:10.3778/j.issn.1002-8331.2011.32.044
基于高斯混合模型的咳嗽音检测方法
Cough sound detection algorithm based on Gaussian mixture model
石锐 1王博 1何庆华2
作者信息
- 1. 重庆大学计算机学院,重庆400030
- 2. 第三军医大学大坪医院野战外科研究所,重庆400042
- 折叠
摘要
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.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Key words
cough sound detection/Mel-frequency cepstral coefficient/Gaussian mixture model/linear combination/wavelet denoise分类
信息技术与安全科学引用本文复制引用
石锐,王博,何庆华..基于高斯混合模型的咳嗽音检测方法[J].计算机工程与应用,2011,47(32):151-154,4.
