Someone asked us "has there been any substantial work to make real-time translation of sign language possible with technology in a bi-directional way."
Interestingly enough, we recently spoke with two different groups participating in the efforts for the translation of sign language in real-time and bi-directional. I've been meaning to share, so here they are...
The first project is a team:
"Had an amazing time at hashtag#startupweekendsingapore and placed second as a team. Very thankful to be with Jerry Tan Si Kai, John Goh, Hyunjung Kim (Cathy Kim), Xinwei Huang. We prototyped Outspoken to translate sign language to text/speech, which can potentially benefit those with hard of hearing to use sign language as their first language to express themselves confidently and comfortably. Also thanks to the help of mentors and friends Mark Lven Palejaro and Albert Puah. SWSG Mega is a very well organised hackathon (and imo has top-notch design) and brings the best experience for all!"
They know about SignWriting, but they currently use spoken language text, rather than sign language text. Their focus on machine learning has a lot of potential when applied to SignWriting text.
The second project is an academia group with dissertations, thesis, and a starting infrastructure. Their central concept is CORE-SL, a linguistic structure for defining sign language. They have mapped out their system which includes real-time and bi-directional processing. These future subsystems depend on their core structures. Their next PHD thesis defense is coming next month I believe.
Link for the PhD
thesis with the formal language to represent SL:
Link for a paper
about the transcoder SLrepresentation - SW (thesis not defended
I believe the
CORE-SL model has many similarities with the SignTyp linguistic
model by Rachel Channon. These models serve different purposes
and have a few key differences.
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