SIGN LANGUAGE RECOGNITION SYSTEM |
Author(s): |
Hitashree A N |
Keywords: |
Sign Language, CNN, RNN |
Abstract |
For those with auditory impairments, sign language is an essential means of communication that acts as a link between the hearing and the deaf communities. In this work, we provide a novel approach that uses CNN or the MediaPipe architecture to recognize sign language in real-time. Robust and precise detection of sign motions is made possible by the combination of CNN networks' sequential modeling capabilities and MediaPipe's hand tracking.The outcomes of our experiment confirm that the recommended approach is efficient at precisely identifying and categorizing real-world sign language gestures. Because of the system's resilience to changes in hand shapes, orientations, and movement rates, it can functional in assistive communication devices, instructional materials, and accessibility technologies for the community of the deaf and hard of hearing.This work advances the development of systems for recognizing sign language by integrating the advantages of MediaPipe for hand tracking and networks or CNN for sequential pattern learning. The suggested method shows potential for enhancing the inclusivity of communication technologies and promoting access to the person with hearing loss. |
Other Details |
Paper ID: IJSARTV Published in: Volume : 10, Issue : 8 Publication Date: 8/6/2024 |
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