Automatic evaluation of hypernasality and consonant misarticulation in cleft palate speech

The automatic evaluation of CP (Cleft Plate) speech has various clinical applications. In this work, automatic classification of hypernasality levels and detection of consonant omission methods are proposed. Considering that the data collection is a major bottleneck in the field of CP speech signal processing, an extensive CP speech database is used. This database is collected over 10 years by the Hospital of Stomatology, Sichuan University, which has the largest number of CLP (Cleft Lip and Palate) patients in China. The vocabulary used for this database covers all the initial consonants and the most widely used vowels in Mandarin. Based on the production process of hypernasality, a two-step classification algorithm is proposed to identify four levels of hypernasality: normal, mild, moderate and severe. In order to locate consonant omission, an effective classification algorithm is proposed through analyzing the acoustic characteristics of initial consonants and finals. The classification accuracy for four hypernasality levels reaches up to 83% and the correct identification of consonant omission is over 94%.