Social signal recognition training platform for people with ASD

Research Student Project
Supervisor name & contact details:
Dr. Brian Vaughan
School of Media
[email protected]
Research Centre Name and Website (if
Digital Media Centre
Please indicate if the intention is to transfer
from the Masters programme to the PhD
programme (if applicable)
Please indicate if the project is suitable for a
self-funded student
Funding Agency
Scholarship Details
Subject Area
Social signal processing
Title of the Project
Social signal recognition training platform for
people with Autism Spectrum Disorder (ASD)
People with ASD have difficulty recognising and responding to facial and auditory social signals.
This project will develop a platform that will train people with ASD to recognise and respond to
basic and complex social signals. The project will use a range of speech and vision technologies
(prosodic accommodation, dimensional emotional representation, openCV, facial action coding
system) to develop a tiered framework, moving from basic to more complex, implemented as a
serious game. The project will utilise facial avatars and speech synthesis to deliver a range of
basic and complex facial and speech expressions to demonstrate different emotional and social
states (angry, happy, sad; sarcastic, humorous etc) in order to enable people with ASD to attain
an increased ability in social interaction. It is envisaged that users will select from a number of
possible answers related to the visual and auditory information on screen, with the goal of
achieving a certain score so they can progress to the next level of training. The training will
consist of a number of tiered levels: visual facial expressions only, auditory vocal expressions
only, and a combination of the two in later, more advanced levels. The project will also
consider the inclusion of a system that will provide real-time feedback related to the facial and
vocal performance of the user as they try to match the multi-modal expressions presented by
the system.
Please indicate the student requirements for this project
Min 2.1 in a masters degree, preferably an MSc. Alternatively, 2.1 or higher in a computer
science/engineering based background. Applicants with a medical qualification or a psychology
qualification will also be considered.
Deadline to submit applications (only for
funded projects)
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