کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
470092 698392 2010 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Automatic diagnosis of vocal fold paresis by employing phonovibrogram features and machine learning methods
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
Automatic diagnosis of vocal fold paresis by employing phonovibrogram features and machine learning methods
چکیده انگلیسی

The clinical diagnosis of voice disorders is based on examination of the rapidly moving vocal folds during phonation (f0: 80–300 Hz) with state-of-the-art endoscopic high-speed cameras. Commonly, analysis is performed in a subjective and time-consuming manner via slow-motion video playback and exhibits low inter- and intra-rater reliability. In this study an objective method to overcome this drawback is presented being based on Phonovibrography, a novel image analysis technique. For a collective of 45 normophonic and paralytic voices the laryngeal dynamics were captured by specialized Phonovibrogram features and analyzed with different machine learning algorithms. Classification accuracies reached 93% for 2-class and 73% for 3-class discrimination. The results were validated by subjective expert ratings given the same diagnostic criteria. The automatic Phonovibrogram analysis approach exceeded the experienced raters’ classifications by 9%. The presented method holds a lot of potential for providing reliable vocal fold diagnosis support in the future.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Methods and Programs in Biomedicine - Volume 99, Issue 3, September 2010, Pages 275–288
نویسندگان
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