• K Poornima Kamath
• Murugesh M S

A vital form of communication for those who are deaf or hard of hearing is sign language, enabling effective expression and interaction. Communication barriers persist due to limited accessibility and understanding of sign language. This system addresses these challenges using Python and Vosk for speech recognition, with Matplotlib for visualization. Google MediaPipe and OpenCV are employed to process and save keypoints during training, which are stored in JSON files for easy access. These keypoints are used to generate sign language actions. The model, trained with a dataset of spoken words mapped to sign language gestures, allows for real-time translation of speech to sign language. This integration provides immediate visual feedback through 2D animation of the sign output, enhancing communication and accessibility.

Sign Language Translation, Computer Vision, Google MediaPipe, Vosk, speech recognition, Matplotlib, 2D animation ploting, Python

"Speech to Sign Language Translator using Python", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.l1-l8, May-2025, Available :http://www.jetir.org/papers/JETIR2505B93.pdf

"Speech to Sign Language Translator using Python", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppl1-l8, May-2025, Available at : http://www.jetir.org/papers/JETIR2505B93.pdf