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Details of Grant 

EPSRC Reference: EP/P02338X/1
Title: Ultrax2020: Ultrasound Technology for Optimising the Treatment of Speech Disorders.
Principal Investigator: Renals, Professor S
Other Investigators:
Cleland nee McCann, Dr J Richmond, Dr K
Researcher Co-Investigators:
Project Partners:
Articulate Instruments Ltd NHS NHS Grampian
Department: Centre for Speech Technology Research
Organisation: University of Edinburgh
Scheme: Standard Research
Starts: 01 August 2017 Ends: 30 November 2021 Value (£): 964,678
EPSRC Research Topic Classifications:
Med.Instrument.Device& Equip. Medical Imaging
EPSRC Industrial Sector Classifications:
Related Grants:
Panel History:
Panel DatePanel NameOutcome
06 Feb 2017 HIPs 2017 Panel Meeting Announced
Summary on Grant Application Form
Speech Sound Disorders (SSDs) are the most common communication impairment in childhood; 16.5% of eight year olds have SSDs ranging from problems with only one of two speech sounds to speech that even family members struggle to understand. SSDs can occur in isolation or be part of disability such as Down syndrome, autism or cleft palate. In 2015, the James Lind Alliance identified improving communication skills and investigating the direction of interventions as the top two research priorities for children with disabilities. Our programme of research aims to fulfil this need by developing technology which will aid the assessment, diagnosis and treatment of SSDs.

Currently in Speech and Language Therapy, technological support is sparse. Through our previous work in the Ultrax project we showed that by using ultrasound to image the tongue in real-time, children can rapidly learn to produce speech sounds which have previously seemed impossible for them. Through this project, we developed technology that enhances the ultrasound image of the tongue, making it clearer and easier to interpret. Ultrax2020 aims to take this work forward, by further developing the ultrasound tongue tracker into a tool for diagnosing specific types of SSDs and evaluating how easy it is to use ultrasound in NHS clinics. The ultimate goal of our research is that Ultrax2020 will be used by Speech and Language Therapists (SLTs) to assess and diagnose SSDs automatically, leading to quicker, more targeted intervention.

Normally speech assessment involves listening to the child and writing down what they say. This approach can miss important subtleties in the way children speak. For example, a child may try to say "key" and it may be heard as "tea". This leads the SLT to believe the child cannot tell the difference between t and k and select a therapy designed to tackle this. However, ultrasound allows us to view and measure the tongue, revealing that in many cases children are producing imperceptible errors. In the above example, an ultrasound scanner placed under the chin shows that the child produces both t and k simultaneously. Identification of these errors means that the SLT must choose a different therapy approach. However, ultrasound analysis is a time consuming task which can only be carried out by a speech scientist with specialist training. It is a key output of Ultrax2020 to develop a method for analysing ultrasound automatically, therefore creating a speech assessment tool which is both more objective and quicker to use.

Building on the work of the Ultrax project, where we developed a method of tracking ultrasound images of the tongue, Ultrax2020 aims to develop a method of classifying tongue shapes to form the basis of an automatic assessment and a way of measuring progress objectively. We are fortunate to already have a large database of ultrasound images of tongue movements from adults and primary school children, including those with speech disorders, on which to base the model of tongue shape classification and to test its performance. At the same time, we will evaluate the technology we develop as part of Ultrax2020 by partnering with NHS SLTs to collect a very large database of ultrasound from children with a wide variety of SSDs. In three different NHS clinics, SLTs will record ultrasound from over 100 children before and after ultrasound-based speech therapy. This data will be sent to a university speech scientist for analysis and feedback to clinicians recommending intervention approaches. Towards the end of the project, we will be able to compare this gold-standard hand-labelled analysis with the automatic classification developed during the project. At the conclusion of our research project we will have developed and validated a new ultrasound assessment and therapy tool (Ultrax2020) for Speech and Language Therapists to use in the diagnosis and treatment of SSDs.
Key Findings
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Potential use in non-academic contexts
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