Projects
Speech-language pathologists (S-LP) play a primary role in the assessment, diagnosis and treatment of children with speech sound disorders. Currently, the assessment process for diagnosis and differential diagnosis of speech sound disorder subtypes requires time consuming administration of several tests (i.e. a test battery approach). This typically includes a case history, oral examination, speech sound assessment (accuracy of child's production of speech sounds) and speech motor testing (precision of speech movements of jaw, lips, tongue etc). These assessments are scored subjectively by listening to child's speech and/or by looking at the child's speech movements, using a pen and paper based approached.
Increasingly, speech science researchers are encouraging S-LPs to integrate objective measures into the assessment process. However, S-LPs face many barriers to achieving this in the clinical setting that include: cost, time, specialist expertise and suitability of the equipment for use with young children. Additionally, expertise to extract and interpret the data is required. These all present as large barriers to S-LPs obtaining objective measures and therefore restrict the capacity to provide an accurate and timely differential diagnosis.
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A preliminary evaluation of the performance of an automated video based facial tracking system with application in speech-language pathology
TEAM: Amar El-Sallam, Roslyn Ward, Paul Davey, Aravind Namasivayam, Geoff Strauss
The purpose of this study is to compare the accuracy of the automated video based tracking system developed by our team, with an optical motion capture system (Vicon Nexus). The Vicon Nexus motion capture system is a three-dimensional tracking system that is considered gold standard. It requires the placement of retro-reflective markers on the face.
In this study, the jaw and lip movements of a typically developing 14 year-old child, were captured using 3 standard off-the-shelf video cameras and eight 4Mp (Vicon) cameras, simultaneously. The child was required to produce 40 words (10 stimulus items per level of the Motor Speech Heirarchy (MSH) and 4 phrases, in response to the instruction "This is a X, say X". The speech movement features have been selected to represent the different speech subsystems and level of control represented in the MSH (Hayden & Square, 1994).
The data was collected in the Motion Analysis Laboratory at Curtin University by a certified practicing S-LP and biomechanist.
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The development and validation of a probe word list to assess speech motor skills in children
TEAM: Aravind Namasivayam, Anna Huynh, Jennifer Hard, Rohan Bali, Vina Law, Francesca Granata, Darshani Rampersaud, Roslyn Ward, Rena Helms-Park, Pascal van Lieshout, Deborah Hayden
The Probe Word Scoring System (PWSS) is designed to measure change in motor speech skills in children either over time or following treatment. The PWSS was originally conceptualized and developed by Ms. Deborah Hayden from the PROMPT Institute in the early 2000s when she noticed the challenges of measuring changes in therapy. Further refinements were carried out in collaboration with the University of Toronto between 2012 and 2020, under the leadership of Dr. Aravind Namasivayam and Dr. Pascal van Lieshout.
They first fine-tuned the word list to address the following factors: (a) Speech Movement Complexity: How difficult are the speech movements used to produce certain words and how many different types of speech movements are needed to produce a word? (b) Language Complexity: How often do the words and sound combinations occur in the child's native language? (c) Word Familiarity: Are the words frequently used in the child's specific environment?
The PWSS was field-tested on 48 preschool and school-aged children with severe speech disorders at clinics across Ontario, Canada and refined once again. This rigorous process has led to the development of the current standardized, reliable, and valid PWSS. The PWSS supports speech therapists in identifying the area of speech motor breakdown in preschool and school-aged children, in setting appropriate goals for therapy, and allows them to measure changes in these therapy goals over time.
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Development of the psychometric properties of the probe word list to assess speech motor skills in children
TEAM: Linda Orton (PhD Candidate), Neville Hennessey, Roslyn Ward, Aravind Namasivayam
The primary aim of this research project is to collect a performance sample of children aged 2 to 4 years to generate normative data and establish the psychometric properties for the Probe Word List and Scoring System (PWSS). As part of her doctoral project, Ms Orton will seek to undertake 3 studies:
Study 1 will involve the collection and analysis of perceptual, acoustic and kinematic measures on the PWSS in order to evaluate the construct validity of the PWSS, and to produce normative data.
Study 2 will further analyse the psychometric properties of the PWSS in accordance with the COSMIN checklist (COnsensus-based Standards for the selection of health status Measurement INstruments).
Study 3 will use a small pilot sample of children with known Speech Sound Disorder to determine the capacity of the PWSS to diagnose motor speech limitations in these children.
This research will provide valuable information about typical speech motor development and will progress the use of facial movements in the assessment and management of motor speech impairment in children with a Speech Sound Disorder.
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Perceptual and acoustic features of typically developing 2 year olds during production of the speech word probes: A pilot study
TEAM: Roslyn Ward, Amar El-Sallam, Sonny Pham, Geoff Strauss, Linda Orton, Aravind Namasivayam, Katie Hustad, Neville Hennessey
The purpose of this study is twofold: 1. explore the acoustic sound (i.e., speech) characteristics of 10 typically developing 2 year-old children, during the production of the Probe Word and Scoring System (PWSS). The acoustic features have been selected to represent the different speech subsystems and level of control represented in the Motor Speech Hierarchy (Hayden & Square, 1994); and 2. compare the acoustic features of interest extracted manually with the proposed method for automated extraction.
Data was collected in the Motion Analysis Laboratory at Curtin University by a certified practicing S-LP. Children produced 40 words (10 stimulus items per level of the MSH) in response to the picture stimulus presented on a large screen, followed by the instruction "This is a X, say X".
The speech acoustic data have been imported into an acoustic analysis package (PRAAT) and the word boundaries manually marked using a combination of spectrographic display, as well as listening to the child's speech. Words that are inaudible or cannot be coded due to background noise will be discarded. The acoustic features of interest include: duration; formant frequencies, ratios and slopes, frication rise time, voice onset time, spectral slope and moments, fricatives and stops.
The acoustic analysis using the PRAAT software package will be compared with the automated speech recognition system developed by our team.
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Sensitivity assessment of the facial landmark placement for longitudinal analysis of speech development
TEAM: Liam Boyle (PhD Candidate), Roslyn Ward, Petra Helmholz, Derek Lichti
Speech sound disorders (SSDs) represent children's most common communication impairment, accounting for approximately 70% of a speech-language pathologist’s (S-LP’s) caseload. Current assessment practices for diagnosing SSDs rely on subjective analyses of error patterns, primarily based on phonetic transcription. However, research suggests that using instrumentation to derive measures of motor speech control (i.e., speech kinematics) may improve the diagnosis of different SSD subtypes. Thus far, the application of these measures has been confined to the research laboratory setting due to cost and equipment constraints. Current developments show that AI based approaches (such as BlazeFace) can help to move the use of kinematic analysis from a research laboratory to clinical practise. This research aims to validate the accuracy of such AI approach for SSD assessments using photogrammetry as a reference. Furthermore, using photogrammetry the study will determine landmarks of significance to extract measurements sensitive to assessing speech motor control. Three specific objectives have been established: 1) determine the optimal camera network to facilitate photogrammetry as an independent method for validation; 2) validate an existing facial landmark algorithm based on AI (e.g., BlazeFace) using photogrammetry; 3) propagate errors to quantify the sensitivity of the facial landmark placement for longitudinal analysis of speech development. The outcomes of this research will provide SL-Ps with a complementary diagnostic approach. This project will be conducted as part of a larger initiative focused on developing a Speech Movement and Acoustic Analysis (SMAAT) software to support speech-language pathologists in diagnosing SSDs.