DocumentCode :
2707044
Title :
Detection of the period of voice based on wavelet
Author :
Guan, Dejun ; Zhong, Yue ; Feng, Jinhan ; Xu, Lisheng ; Wang, Liping
Author_Institution :
Shenyang Radio & Telev. Univ., Shenyang, China
fYear :
2012
fDate :
6-8 June 2012
Firstpage :
876
Lastpage :
881
Abstract :
The quality analysis of pathological voice is not only a kind of objective evaluation for the human voice, but also an objective evidence for the application of voice disease diagnosis and the judgment of therapy. In this paper, the pathological voice quality analysis system is composed of five parts, which are voice recording, voice signal processing, and extraction of voice characteristic parameters, choice of these features and evaluation of voice quality. Firstly, this paper gives a brief introduction to the pathological voice quality analysis´s background and purpose. Besides, it also details some methods of voice signal processing. For detection of voice period, vague fundamental frequency of voice is extracted firstly by using Fourier transform, and then the accurate detection of the voice period through EGG and wavelet transformation is performed. This method of period detection is highly accurate and practicable. Based on the period of voice, many features of voice such as the fundamental frequency, frequency perturbation, and amplitude perturbation can be extracted. This database is built by collecting healthy and pathological voice samples from Shengjing Hospital and related references. After analyzing the collected voice signals, the result shows that the pathological voice quality analysis system has the well evaluation performance in the practical application. These evaluation results reflect the quality of voice signal and can be used to assistant judge the treatment of voice disease and the recovery condition of treatment.
Keywords :
Fourier transforms; medical signal processing; patient treatment; speech processing; wavelet transforms; EGG; Fourier transform; Shengjing hospital; amplitude perturbation; frequency perturbation; human voice; pathological voice quality analysis; therapy judgment; treatment recovery condition; voice characteristic parameter extraction; voice disease diagnosis; voice period detection; voice recording; voice signal processing; wavelet transformation; Diseases; Feature extraction; Frequency domain analysis; Medical diagnostic imaging; Pathology; Wavelet analysis; Wavelet transforms; EGG; Fundamental Frequency; Voice Quality Analysis; Wavelet Transformation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Automation (ICIA), 2012 International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4673-2238-6
Electronic_ISBN :
978-1-4673-2236-2
Type :
conf
DOI :
10.1109/ICInfA.2012.6246905
Filename :
6246905
Link To Document :
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