Sign On, led by PI and ADAPT researcher Andy Way, will research and develop the SignON communication service that uses machine translation to translate between Sign and spoken languages. This service will facilitate the exchange of information among deaf and hard of hearing, and hearing individuals. In this user-centric and community-driven project the project team will tightly collaborate with European deaf and hard of hearing communities to (re)define use-cases, co-design and co-develop the SignON service and application, assess the quality and validate their acceptance.
The project will develop a free, open application and framework for conversion between video (capturing and understanding Sign language), audio and text and translation between Sign and spoken languages. To ensure wide uptake, improved sign language detection and synthesis, as well as multilingual speech processing on mobile devices for everyone, the project will deploy the SignON service as a smart phone application running on standard modern devices.
SignON will incorporate sophisticated machine learning capabilities that will allow learning new Sign, written and spoken languages, style, domain- and user-adaptation and automatic error correction, based on user feedback. The project’s ultimate objective is the fair, unbiased and inclusive spread of information and digital content in European society.
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If your research touches on this problem then the newly launched €65 million SFI National Challenge Fund is looking for ambitious researchers who are ready for a challenge.