Event-Based Transformation of Misarticulated Stops in Cleft Lip and Palate Speech

Abstract

The cleft of the lip and palate (CLP) is a congenital disability affecting the craniofacial region and it impacts the speech production system. The current work focuses on the modification of misarticulations produced for unvoiced stop consonants in CLP speech. Three types of misarticulations are studied: glottal, palatal, and velar stop substitutions. The stop consonants are misarticulated due to inadequate buildup of intra-oral pressure caused by velopharyngeal dysfunction and oro-nasal fistula. The misarticulated stops affect the speech intelligibility and quality, and this further affects the use of speech-based applications. The misarticulated stops are analyzed and modified using the speech data collected from 60 Kannada speaking children (normal and CLP). An event-based modification approach is used to correct the misarticulated stops. At first, automatic detection of burst onset and vowel onset events is carried out. Then, the region from vowel onset to 20 ms duration of the vowel is extracted. Further, the region from burst onset point to 20 ms duration of the vowel is defined as the region for modification. It is transformed using the nonnegative matrix factorization (NMF) method. The objective and subjective evaluation results show that the proposed event-based transformation approach provides a relative improvement compared to the entire-word modification (signal processed without using the knowledge of burst and vowel onset events). The event-based transformed misarticulated stops showed close similarity with the normal stops in perceptual quality. The improved performance accuracy of modified stops suggests that the speech distortion is minimized.