Title :
Automatic Voice Quality Measurement Based on Efficient Combination of Multiple Features
Author :
Lee, Ji-Yeoun ; Jeong, Sangbae ; Hahn, Minsoo ; Choi, Hong-Shik
Author_Institution :
Inf. & Commun. Univ., Daejeon
Abstract :
This work proposes higher-order statistics (HOS)- based features to improve classification performance of voice quality measurement. They are means and variances of skewness and kurtosis which show meaningful differences in normal, breathy, and rough voices. Jitter, shimmer, and harmonic to noise ratio (HNR) are implemented as conventional features. The performances are measured by classification and regression tree (CART) analysis. Specifically, the CART-based method by utilizing both conventional and HOS-based features is shown to be an effective for voice quality measurement, with an 89.7% classification rate.
Keywords :
feature extraction; medical signal processing; patient diagnosis; regression analysis; signal classification; speech; speech processing; automatic voice quality measurement; breathy voices; classification and regression tree analysis; harmonic to noise ratio; higher-order statistics; jitter; kurtosis; multiple features; normal voices; rough voices; shimmer; skewness; voice classification; Acoustic measurements; Classification tree analysis; Higher order statistics; Jitter; Pathology; Performance analysis; Performance evaluation; Regression tree analysis; Signal to noise ratio; Vibration measurement;
Conference_Titel :
Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-1747-6
Electronic_ISBN :
978-1-4244-1748-3
DOI :
10.1109/ICBBE.2008.646
