Feature Extraction for Cough-sound Recognition Based on Principle Component Analysis and Non-uniform Filter-bank.
- Author:
Chumei ZHU
;
Hongqiang MO
;
Lainfang TIAN
;
Zeguang ZHENG
- Publication Type:Journal Article
- MeSH:
Cough;
Humans;
Markov Chains;
Principal Component Analysis;
Respiratory Tract Diseases;
diagnosis;
Sound
- From:
Journal of Biomedical Engineering
2015;32(4):746-750
- CountryChina
- Language:Chinese
-
Abstract:
Cough recognition provides important clinical information for the treatment of many respiratory diseases. A new Mel frequency cepstrum coefficient (MFCC) extracting method has been proposed on the basis of the distributional characteristics of cough spectrum. The whole frequency band was divided into several sub-bands, and the energy coefficient for each band was obtained by method of principle component analysis. Then non-uniform filter-bank in Mel frequency is designed to improve the extracting process of MFCC by distributing filters according to the spectrum energy coefficients. Cough recognition experiment using hidden Markov model was carried out, and the results
