Automatic detection of articulation disorders in children with cleft lip and palate

• Published in: The Journal of the Acoustical Society of America Vol. 126; no. 5; pp. 2589 - 2602
• Main Authors: Maier, Andreas, Hönig, Florian, Bocklet, Tobias, Nöth, Elmar, Stelzle, Florian, Nkenke, Emeka, Schuster, Maria
• Format: Journal Article
• Language: English
• Published: Melville, NY Acoustical Society of America 01-11-2009; American Institute of Physics
• Subjects: Algorithms; Articulation Disorders - diagnosis; Articulation Disorders - etiology; Biological and medical sciences; Child; Cleft Lip - complications; Cleft Palate - complications; Ear and associated structures. Auditory pathways and centers. Hearing. Vocal organ. Phonation. Sound production. Echolocation; Fundamental and applied biological sciences. Psychology; Humans; Models, Biological; Phonation; Phonetics; Psycholinguistics; Speech Therapy; Vertebrates: nervous system and sense organs; Human; Palate; Speech articulation; Disordered system; Automatic measurement; Child
• ISSN: 0001-4966; 1520-8524
• DOI: 10.1121/1.3216913

Speech of children with cleft lip and palate (CLP) is sometimes still disordered even after adequate surgical and nonsurgical therapies. Such speech shows complex articulation disorders, which are usually assessed perceptually, consuming time and manpower. Hence, there is a need for an easy to apply and reliable automatic method. To create a reference for an automatic system, speech data of 58 children with CLP were assessed perceptually by experienced speech therapists for characteristic phonetic disorders at the phoneme level. The first part of the article aims to detect such characteristics by a semiautomatic procedure and the second to evaluate a fully automatic, thus simple, procedure. The methods are based on a combination of speech processing algorithms. The semiautomatic method achieves moderate to good agreement
(
κ
≈
0.6
)
for the detection of all phonetic disorders. On a speaker level, significant correlations between the perceptual evaluation and the automatic system of 0.89 are obtained. The fully automatic system yields a correlation on the speaker level of 0.81 to the perceptual evaluation. This correlation is in the range of the inter-rater correlation of the listeners. The automatic speech evaluation is able to detect phonetic disorders at an experts'level without any additional human postprocessing.