کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4943250 | 1437624 | 2017 | 45 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Detection of different voice diseases based on the nonlinear characterization of speech signals
ترجمه فارسی عنوان
تشخیص بیماری های مختلف صوتی بر اساس ویژگی غیرخطی سیگنال های گفتاری
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
This work describes a novel methodology to characterize voice diseases by using nonlinear dynamics, considering different complexity measures that are mainly based on the analysis of the time delay embedded space. The feature space is represented with a DHMM and a further transformation of the DHMM states to a hyperdimensional space is performed. The discrimination between healthy and pathological speech signals is peformed by using a RBF-SVM which is trained following a K-fold cross-validation strategy. Results of around 99% of accuracy are obtained for three different voice disorders, disphonia due to laryngeal pathologies, hypernasality due to cleft lip and palate, and dysarthria due to Parkinson's disease.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 82, 1 October 2017, Pages 184-195
Journal: Expert Systems with Applications - Volume 82, 1 October 2017, Pages 184-195
نویسندگان
Carlos M. Travieso, Jesús B. Alonso, J.R. Orozco-Arroyave, J.F. Vargas-Bonilla, E. Nöth, Antonio G. Ravelo-GarcÃa,