TRANSLOK-indian language translator.pptx

Translok - indian language translator

1. TRANSLOK INDIAN LANGUAGE TRANSLATOR

2. Guided By: Rameez Mohammed A Submitted by: Amritha Gireesh (PKD20CS010) Amritha K (PKD20CS011) Anusree E (PKD20CS016) Kavya CV (PKD20CS036)

3. INTRODUCTION India is a country of multilinguistic languages, so communication can often pose a significant challenge.This has led to the development of a translation app using advanced machine learning techniques, aiming to bridge the linguistic gap and improve understanding and accessibility in the country.

4. PROBLEM DEFINITION The challenge at hand is to design and implement a translation app tailored for India, employing machine learning to overcome Linguistic Variability, Contextual Understanding, User Accessibility and Continuous Learning. One of the most common problems that people have to face while traveling around the world is the language barrier. There is a communication gap, and travelers find it difficult to understand the native language while interacting with the locals.

5. ABSTRACT India, a multilingual nation, faces a linguistic gap between its states. To bridge this, an AI-based picture and text translation application is introduced. The app translates texts into a preferred language, allowing users to capture images containing text, signage, or documents. This innovative solution not only addresses immediate communication challenges but also contributes to fostering inclusivity and cultural exchange. The app's potential impact extends to educational, business, and governmental sectors, where effective communication is pivotal.

6. OBJECTIVE The primary objectives of the project are: Develop a Multilingual Translation Model Implement Context-Aware Translation Comprehensive Language Support Design a User-Friendly Interface Enable Continuous Improvement

7. ARCHITECTURE DIAGRAM

8. HARDWARE AND SOFTWARE TOOLS Device – Laptops,Smart Phone Programming Language-Dart IDE- Android Studio Framework-Flutter API - Google translate API

9. MODULES User Interface(UI) Input Processing Translation Engine Output Rendering Text-to-Speech(TTS)

10. UI/UX DESIGN Welcome page Text-To-Text Translate Splash screen

11. UI/UX DESIGN Image Scanner

12. RESULT

13. RESULT

14. ACTION PLAN January February March April May Data preparation & preprocessing UI/UX interface design Text-to-Text Integration Text-to-voice integration Image-to-text Integration App deployment and Testing Final review

15. FUTURE SCOPE Language Learning: These apps can be integrated into language learning platforms to assist students in learning new languages more effectively by translating text from images. Language Barrier: Facilitate communication between healthcare professionals and patients who speak different languages by translating medical documents or prescriptions. E-commerce: Enhance user experience on e-commerce platforms by allowing users to extract text information from product images, such as product descriptions, reviews, and specifications.

16. FUTURE SCOPE Translation Services: Help tourists navigate and understand local languages by translating signboards, menus, and other text from images. Citizen Services: Facilitate government communication with citizens by translating important information, announcements, and documents into multiple languages. Public Safety: Enhance public safety by translating emergency instructions and warnings into various languages during natural disasters or public emergencies.

17. CONCLUSION The development of the Translation App for India using advanced machine learning techniques marks a significant milestone in overcoming the linguistic challenges prevalent in our culturally rich and diverse nation. This project was initiated with the recognition that effective communication is not just a matter of linguistic exchange but a bridge that connects people across different languages and dialects.

18. REFERENCE [1] An Integrated Model For Text to Text, Image to Text and Audio to Text Linguistic Conversation Using Machine Learning Approach-IEEE(2023) [2] Image to Multilingual Text Conversion for Literacy Education-IEEE(2018) [3] A simple Translation System using a Machine Learning Algorithm-IEEE(2023) [4] Comparative Study of Text-to-Speech Synthesis Techniques for Mobile Linguistic Translation Process-IEEE(2014)

19. THANK YOU