gesture listen for the def and dem poeples.pptx

this is a project that helps to the disable peoples

1. GESTURE LISTEN Department of Computer Science and Engineering Team Members 1. Shridharan R B (20uad008) 2. Srikumbesh S (20uad036) 3. Zawahar S (20uad022) Project Guide Mr. B.Muthukrishna Vinayagam AP/CSE TECHNOVISION 2K24 Project ID: AD013

2. Motivation for the Project In an increasingly interconnected world, effective communication is essential for social inclusion and collaboration. However, individuals with speech or hearing impairments often face barriers in expressing themselves digitally. "Gesture Listen" addresses this challenge by offering a groundbreaking web-based platform that facilitates seamless communication between individuals with impairments and others. Gesture Listen aims to enhance accessibility and foster greater understanding and integration within diverse communities, ultimately empowering individuals to communicate fluently and inclusively in a digital environment.

3. Project Proposal Document Project Description Develop a comprehensive solution that enables the conversion of spoken audio content into sign language, catering to the needs of the hearing-impaired community. Gesture Listen aims to enhance accessibility for individuals who are deaf or hard of hearing.

4. Project Proposal Document Innovation By using JavaScript Web speech API for Speech recognition. By using 3D animation of a character created using Blender 3D tool. Applications Assistive Technology: Integrating sign language detection into assistive devices such as smartphones, tablets, and wearables to empower users in daily activities.

5. Literature Survey (Maximum of 1 slide) Author Name Name of the Journal Title of the Paper Year of Publication Inference chadda reddy,vadhhiraju swathi,nomulla pravikka International Journal On Engineering Technology Audio to sign language translator 2023 Back Propagation neural network (BPNN) and SVM Charge coupled device camera is used S.srenika, M.madhubala International Journal On Engineering Technology Sign languge translator using templates 2020 Accuracy obtained was 88.93% NLP Ankita harkude,Sarika namade Usha Mittal institute of technology Audio to sign language for deaf people 2020 NLP API

6. Design Document Sl.no` Nature of work Duration 1. Preparing 3D Avatar 1 week 2. Audio recognition 1 week 3. NLP Processing 2 weeks 4. Final Demo 2 weeks 5. Documentation of the work 1 week Work Breakdown Structure A. Development Plan

7. GANTT CHART Activities Time (Weeks) W1 W2 W3 W4 W5 W6 W7 W8 W9 W10 W11 W12 Data collection, Text Preprocessing Design of Front-end Development Design of Speech Recognition Integration Integration and Testing Deployment and Maintenance

8. B. Design Project Requirements Sl.no Requirements 1 Django Frameworks 2 3D Avatar

9. System Configuration SETUP DIAGRAM OF GESTURE LISTEN

10. D. OUTPUT:

11. References Vaddhiraju Swathi, Chada Gautham Reddy, Nomula Pravallika, P. Varsha Reddy, Ch. Prakash Reddy, Audio To Sign Language Converter Using Python 01-2023. S. Shrenika and M. Madhu Bala, \"Sign Language Recognition Using Template Matching Technique,\" 2020 International Conference on Computer Science, Engineering and Applications (ICCSEA), Gunupur, India, 2020, pp. 1-5, doi: 10.1109/ICCSEA49143.2020.9132899. Ankita Harkude#1, Sarika Namade#2, Shefali Patil#3, Anita Morey #4, Department of Information Technology, Usha Mittal Institute of Technology, Audio to Sign Language Translation for Deaf People, (IJEIT) Volume 9, Issue 10, April 2020. Amit Kumar Shinde and Ramesh Khagalkar “sign language to text and vice versa recognization using computer vision in Marathi” International journal of computer Application (0975-8887) National conference on advanced on computing (NCAC 2015).