Nonlinear feature extraction of pathological voice based on the human ear filter bank
Konferenz: BIBE 2018 - International Conference on Biological Information and Biomedical Engineering
06.06.2018 - 08.06.2018 in Shanghai, China
Tagungsband: BIBE 2018
Seiten: 7Sprache: EnglischTyp: PDFPersönliche VDE-Mitglieder erhalten auf diesen Artikel 10% Rabatt
Xu, Yuanjing; Hu, Weiping; Liang, Dongdong (Guangxi Normal University, Guangxi, China)
Wang, Houying (Guangxi Normal University, Guangxi, China & Beihai Vocational College, Guangxi, China)
The nonlinear features of voices can effectively distinguish normal and pathological voices; however, feature extraction is a time-consuming process, which is unfavorable for real-time processing. This study aims to reduce the time of feature extraction based on nonlinear features to either maintain or improve the rate of pathological voice recognition. A method based on the human ear filter bank is proposed to optimize the extraction of nonlinear characteristics of pathological voice. In the extraction process, feature optimization is achieved by extracting the nonlinear features of a certain frequency band. The results show that the method based on the human ear filter bank greatly shortens the extraction time and typically acquires a higher rate of parameter identification than the traditional methods.