HandsIn x CLERC: Building the Future of Sign Language Learning
CLERC is partnering with HandsIn, the ASL learning platform, to power its sign recognition with data recorded by native Deaf signers. HandsIn launches on the web on October 5, with sign recognition trained on the CLERC corpus.
For us, this is more than a data deal. It is proof of something we have believed since day one: sign language AI is not only about translation. It is also about how the next generation learns to sign.
What is HandsIn?
HandsIn is an accessible ASL learning platform, founded by Marlena and Grace. It uses real-time sign language recognition to give learners instant feedback on how well they reproduce each sign.
- Built with Deaf teachers. Every lesson video features Deaf native ASL signers with teaching experience, filmed in HandsIn's own studio.
- Active practice, not passive watching. Lessons use contextual clues, active recall and repetition, so learners sign instead of just watching.
- Deaf culture in every lesson. Culture is woven into the curriculum, not added as a side note.
Data built for training, not for archives
CLERC records and annotates American Sign Language with native Deaf signers. Every signer is paid, and every signer has consented to how their data is used. The annotation goes deep enough to train models on, not just to catalog videos.
That is exactly what HandsIn needed: sign language data it is allowed to train on, from the people who actually use the language. In HandsIn's own words:
"This partnership gives us stronger data and a way to extend recognition across more signs, and it reflects a priority we have held from the beginning: building with Deaf expertise at the center."
CLERC was founded and is led by Florian Méloux, who is Deaf and a native signer. Deaf expertise is not a feature we add on top. It is how the corpus is built, from the prompts to the final quality check.
Beyond translation: education
CLERC was designed for this. The same corpus that helps build sign language translation can also teach. A model that recognizes signs accurately can tell a learner, in real time, whether their sign is right, and what to fix.
Translation helps Deaf and hearing people talk to each other today. Education makes sure more hearing people can sign tomorrow. We want our data to serve both.
HandsIn is the first learning platform to train on CLERC data.
The future of sign language learning
Learning to sign has long depended on having a teacher in the room. AI changes that, but only if the model learned from the right people. A learner who practices against a model trained on native Deaf signers learns the language as the Deaf community actually signs it.
That is the platform we see coming: one that brings the Deaf world and the hearing world together. Hearing learners get feedback they can trust. Deaf signers see their language taught on their terms, and are paid for the expertise they bring.
"The model that checks a learner's sign on HandsIn learned from native Deaf signers who were paid and gave their consent. So when a hearing learner gets feedback, it reflects ASL as Deaf people actually sign it. That is what CLERC was built for. But this goes beyond our work. I am convinced that this is how the Deaf and hearing worlds come together: one learner, one sign, one conversation at a time. On a personal level, I am truly happy to contribute to that."
Florian Méloux, founder and CEO of CLERC
A partnership built to last
This collaboration is designed for the long run. As HandsIn adds new modules, CLERC records and annotates the signs they need, and HandsIn's recognition grows with each one.
Try it yourself. The best way to see what this partnership makes possible is to sign. HandsIn is free on the web during its early launch. Start a module and get instant feedback on your signs at handsinlearning.co.
We are proud to support a team that put Deaf expertise at the center from the start. If you are building a product that needs sign language data you are allowed to train on, for translation or for education, get in touch with CLERC.