The project uses video recordings to capture sign language gestures, which are processed into a structured dataset. Through training with a Random Forest classifier and integration with Azure and OpenAI, the system accurately interprets sign language and applies real-time corrections. Its goal is to enable seamless communication for the deaf and hard-of-hearing communities, fostering inclusivity and breaking down barriers.

[AryanRana07]

Project name

Hand Sign To Text

Description

The project aims to enhance communication accessibility for the deaf and hard-of-hearing communities by leveraging advanced technology. It begins with capturing sign language gestures through video recordings, which are then processed and serialized using pickling techniques to create a structured dataset. This dataset undergoes training with a Random Forest classifier to recognize and interpret sign language gestures accurately. Furthermore, integration with Azure and OpenAI enhances the solution with an Auto-Correct mechanism, refining outputs in real-time. Ultimately, the project strives to empower individuals with seamless communication, breaking down barriers and fostering inclusivity

Project Repository URL

https://github.com/AryanRana07/Fabric-Hackathon

Project video

https://drive.google.com/file/d/1V8gfirdk-lkcphkI759cZrXKBP85dW7B/view?usp=sharing

Team members

AryanRana07, gourav312, Cycl0tr0n

[AryanRana07]

Final Submission