PATHOLOGICAL ASSESSMENT OF VOCAL FOLD NODULES AND POLYP VIA FRACTAL DIMENSION OF PATIENTS VOICES
In this paper, we are going to evaluate the role of nonlinear feature, fractal dimension, in discriminating patients with speech disorders from normal subjects. Laryngeal pathologies usually cause an asymmetry in oscillation of vocal folds. This leads to sub-harmonics and chaos in generated voices. In such condition, using nonlinear dynamic features, like fractal dimension, seems to be efficient approach to analyze understudied voice. To calculate fractal dimension of voice sample, we exploit two methods of Petrosian and Katz and compare them with each other. Moreover, in order to evaluate role of frequency sub-bands in diagnosis process, voice signals are decomposed into two subbands by wavelet filter bank and fractal features extracted distinctively for each band. To simplify current work, we only conduct our experiments on discriminating nodule and polyp disorders from normal subjects. The best classification result is obtained 88.9％ using combination of fractal dimensions of voices and their sub-bands.
Vocal Fold Pathology Fractal Dimension Petrosian Method Katz Method Support Vector Machine
Ghazaleh vaziri Farshad Almasganj
Faculty of Biomedical Engineering Amirkabir University of Technology Tehran, Iran
国际会议
上海
英文
2044-2047
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）