关键词: 腭裂语音, 咽擦音, 分段指数压缩, Gammatone滤波器组, SSMC模型

Abstract: Pharyngeal fricative in cleft palate speech is a common compensatory consonant anomaly. The automatic detection of pharyngeal fricatives has important clinical significance for the evaluation of pharyngeal function. In this work, an automatic detection algorithm in cleft palate speech has been researched. Piecewise Exponent Compression Gammatone Filters（PECGTFs） and Softsign-based Multi-Channel（SSMC） model are combined to extract the spectral feature parameters of speech signal, and KNN classifier is used to realize the automatic detection of pharyngeal fricatives in cleft palate speech. Experimental data includes 306 speech samples. The results of using different gammatone filters, Difference of Gaussian（DoG） enhancement and SSMC model enhancement on the automatic detection results of pharyngeal fricatives in cleft palate speech are compared. The automatic detection accuracy of pharyngeal fricatives in cleft palate speech using the algorithm proposed in this paper is 94.95%, which has certain reference value for clinical diagnosis.

Key words: cleft palate speech, pharyngeal fricatives, piecewise exponent compression, Gammatone filters, Softsign-based Multi-Channel（SSMC） model