Language Translator Only for Telugu, English using Deep Learning

Project Code :TCMAPY1124

Objective

The objective of this project is to develop a language translator specifically tailored for translating between Telugu and English using Long Short-Term Memory (LSTM) neural networks. By leveraging a dataset containing parallel sentences in Telugu and English, we aim to train and evaluate the LSTM model to achieve accurate and fluent translations. The ultimate goal is to provide users with an efficient tool for bridging the language gap between Telugu and English speakers.

Abstract

ABSTRACT

The Language Translator for English, Hindi, Telugu, and Kannada is an innovative application designed to bridge linguistic gaps by providing seamless translation services across text, speech, and images. The system incorporates three core modules: Text Translation, Voice (Audio-Speech) Translation, and Text Extraction from Image Translation. Users can translate English text into Hindi, Telugu, or Kannada, while the audio translation module enables bi-directional speech-to-text translation among the four supported languages. The image translation module leverages Optical Character Recognition (OCR) to extract English text from images and translate it into the target language. This project employs cutting-edge natural language processing (NLP) technologies such as Hugging Face MarianMT models for high-quality translations, Google’s Text-to-Speech (gTTS) for audio output, and SpeechRecognition for accurate speech-to-text conversion. The application is implemented using the Flask framework, ensuring a scalable and user-friendly interface. Additionally, fallback mechanisms like Google Translate (via the googletrans library) ensure consistent performance across use cases. The system is designed to cater to a broad audience, including professionals, educators, travelers, and multilingual communities, addressing real-world challenges in communication. With its focus on accuracy, simplicity, and versatility, this translator enables efficient interaction in multilingual environments, enhancing accessibility and breaking down language barriers. This document outlines the system's architecture, implementation methodologies, and the role of each module, providing a comprehensive understanding of its capabilities and potential applications.

Keyword: Language Translator, Telugu, English, Kannada, Telugu.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.