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The machine translation of sign languages has been possible, albeit in a limited fashion, since 1977. When a research project successfully matched English letters from a keyboard to ASL manual alphabet letters which were simulated on a robotic hand. These technologies translate signed languages into written or spoken language, and written or spoken language to sign language, without the use of a human interpreter. Sign languages possess different phonological features than spoken languages, which has created obstacles for developers. Developers use computer vision and machine learning to recognize specific phonological parameters and epentheses[1] unique to sign languages, and speech recognition and natural language processing allow interactive communication between hearing and deaf people.
^Mocialov, Boris; Turner, Graham; Lohan, Katrin; Hastie, Helen (2017). "Towards Continuous Sign Language Recognition with Deep Learning" (PDF). Creating Meaning with Robot Assistants: The Gap Left by Smart Devices (IEEE-RAS International Conference on Humanoid Robots). S2CID 5525834. Archived from the original (PDF) on 2021-01-10. Retrieved 2020-05-04.
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