کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
505772 864535 2007 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Wavelet time-frequency analysis and least squares support vector machines for the identification of voice disorders
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Wavelet time-frequency analysis and least squares support vector machines for the identification of voice disorders
چکیده انگلیسی

This work describes a novel algorithm to identify laryngeal pathologies, by the digital analysis of the voice. It is based on Daubechies’ discrete wavelet transform (DWT-db), linear prediction coefficients (LPC), and least squares support vector machines (LS-SVM). Wavelets with different support-sizes and three LS-SVM kernels are compared. Particularly, the proposed approach, implemented with modest computer requirements, leads to an adequate larynx pathology classifier to identify nodules in vocal folds. It presents over 90% of classification accuracy and has a low order of computational complexity in relation to the speech signal's length.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers in Biology and Medicine - Volume 37, Issue 4, April 2007, Pages 571–578
نویسندگان
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