Computational modelling of sign languages aims to develop technologies that can serve as means for understanding (i.e., recognising) and producing (i.e., generating) a particular sign language. This field of research aims to provide the technological means for two-way mediated communication between hearing and deaf people. However, research on the computational modelling of sign languages is still in its infancy.
This PhD project aims to design, formalise, develop and evaluate technologies for the automatic generation of Australian Sign Language. The invented technologies will be an essential step towards a wide range of applications that will assist in Australian Sign Language communication and education (e.g., applications that support acquisition and training of sign language skills), thus will enhance awareness, facilitate inclusion, participation and equality, and improve access for people who are deaf or hard of hearing.
This PhD project will invent the first Australian Sign Language generator to synthesise 1000+ signs. The project’s goal is three-fold: (1) To increase the amount and variation of signs in the available structured Australian Sign Language data, thus addressing both the problem of bias in data and learning and structured data scarcity, (2) To increase the engagement with the generated sign language content through controllable physical appearance, thus increasing the probability of positive educational outcomes, and (3) To increase the intelligibility of the generated sign language content through controllable signing style, thus decreasing the mental effort for mediated sign language communication.
Please apply before 15 December 2022.
In addition to excellent numerical and programming skills, previous experience in Computer Vision, Machine Learning, Deep Learning, Computer Graphics, and Australian Sign Language would be highly advantageous.