基于递归图分析的腭裂语音鼻漏气自动识别算法

doi:10.11896/jsjkx.181001848

Abstract

Abstract: Nasal leak is a typical symptom of patients with velopharyngeal insufficiency.This paper studied the characteristics of nasal leak in cleft palate speech.Recursive plot based on the nonlinear dynamics method is used to explore the features.Combined with the recursive trend analysis method and the region distribution processing based on the recursive plot, quantitative parameters and minimum regions of the recursive plot analysis are extracted as characteristic matrix.Combined with classifier,automatic detection of nasal leak in cleft palate speech is achieved.The experiment analyzes the detection effect for factors such as downsampling point,delay time,critical distance,speech unit and classifier type then comprehensively weighs the influence of each factor on the detection accuracy in order to select the optimal value.The experimental results show that when the KNN classifier is used,the downsampling point is 30000 points,the delay time is 3ms,the critical distance is 5 units,and the speech unit is 4 frames,the detection accuracy of nasal leak in cleft palate speech is 84.63%.The automatic detection algorithm of nasal leak in cleft palate speech is aimed at providing an effective and objective auxiliary diagnosis basis for clinical pharyngeal function assessment.

Key words: Cleft palate speech, Nasal leak, Recursive plot, Region distribution

CLC Number:

TP391.9

LIU Xin-yi,TIAN Wei-wei,LIANG Wen-ru,HE Ling,YIN Heng. Automatic Detection Algorithm of Nasal Leak in Cleft Palate Speech Based on Recursive Plot Analysis[J].Computer Science, 2020, 47(2): 95-101.

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Automatic Detection Algorithm of Nasal Leak in Cleft Palate Speech Based on Recursive Plot Analysis

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