| Abstract |
In crisis situations, effective communication is vital, yet Irish Sign Language (ISL) users face significant barriers when interacting with emergency services, which primarily understand only a fraction of the population. Research indicates a profound lack of ISL proficiency among emergency responders, often relegating ISL users to reliance on others for communication, thereby risking dehumanisation and heightened danger, especially in cases of crime or domestic violence. This project proposes the development of the "Secure Hands" app, designed to bridge the communication gap through machine learning and text-to-speech technology. The app aims to interpret basic ISL gestures into text for responders, while also verbally conveying messages aloud.
Before engagement, ISL users will receive instructional videos and texts explaining the app's function. The app will incorporate incentivised learning features to educate emergency responders on ISL phrases. A comprehensive literature review and quantitative surveys have highlighted the urgent need for such a solution. Collaborations with experts in app development and ISL users have informed the app’s design, ensuring it meets the community’s needs.
Initial prototypes using Teachable Machines will transition to TensorFlow for enhanced capabilities. The app’s efficacy will be evaluated through trials involving both emergency responders and ISL users in simulated emergencies, followed by quantitative and qualitative feedback. This innovative approach aims to significantly reduce communication barriers, thereby improving safety and accessibility for the ISL community within emergency service contexts.
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