BACKGROUND: Children with cleft lip and palate (CLP) often continue to have problems producing clear speech long after the clefts have been surgically repaired, leading to educational and social disadvantage. Speech is of key importance in CLP from both a quality of life and surgical outcome perspective, yet assessment relies on subjective perceptual methods, namely phonetic transcription. This is particularly problematic in CLP where the range of error types is arguably far greater than for other speech sound disorders, leading to problems with reliability (Howard & Lohmander, 2011). Moreover, CLP speech is known to be vulnerable to imperceptible error types, such as double articulations which can only be understood with instrumental techniques. Incorrect transcription of these errors can result in misdiagnosis and subsequent inappropriate intervention which can lead to speech errors becoming deeply ingrained. Until now, the technique of choice (recommended by the UK professional body for Speech & Language Therapists) for assessing articulatory errors in CLP has been electropalatography, with a number of small n studies showing it to be a powerful technique for identifying imperceptible errors and treating them by using real-time EPG for biofeedback. However, EPG is expensive and logistically difficult to manage. In contrast, ultrasound is cheaper and arguably better equipped to image the posterior articulations (such as pharyngeals) which are common in CLP. This study will present an ultrasound assessment protocol for the assessment of CLP speech which is designed to dovetail with current assessment practices used in Europe. Methods: We will use UTI to both qualitatively and quantitatively identify errors in the speech of 40 children with CLP. Data will consist of materials from the CLEFTNET protocol: spontaneous counting, 10 repetitions of all consonants in /aCa/, sentences from GOS.SP.ASS. 98 (Sell, Harding & Grunwell, 1998) and 5 minimal sets contrasting common substitutions (e.g. “a ship, a sip, a chip”). Ultrasound data will be collected using a Sonospeech high-speed cineloop system at 80fps over a 150 degree field of view. The ultrasound probe will be placed under the chin using a new lightweight stabilising head set. Analysis: Consonants will be annotated using Articulate Assistant Advanced (AAA) software (Articulate Instruments, 2012), after which we will systematically analyse the data to identify each of Gibbon’s eight error types (Gibbon, 2004) using measures by Zharkova (2013, 2016) and Dawson, Tiede and Whalen (2016).Conclusions: Data collection is ongoing. This poster will present the protocol for the study and some preliminary data demonstrating cleft-type speech characteristics which can be identified using ultrasound.
|Publication status||Published - 4 Oct 2017|
|Event||Ultrafest VIII - Potsdam, Germany|
Duration: 4 Oct 2017 → 6 Oct 2017
|Period||4/10/17 → 6/10/17|
- speech assessment
- speech disorders
- cleft palate speech