Generative AI-based translation tools suite
Date
2026-01
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
BRAC University
Abstract
This project presents the design and development of an intelligent document translation
and preview system capable of handling multi-format files including Word, Excel,
text, and images. The system integrates Optical Character Recognition (OCR),
automated translation, and interactive preview functionalities within a unified interface.
A dynamic tab-based architecture allows users to manage multiple translation
sessions simultaneously, with real-time state management ensuring synchronization
between the client and server.
The system leverages modern large language models (LLMs), such as the Gemini
API, to perform context-aware translations. To enhance efficiency, the backend implements
asynchronous batching and batched API calls, minimizing latency during
large-scale translation tasks. The chat assistant module provides contextual editing
support and instruction-based translation refinement, allowing users to iteratively
improve outputs without manual re-uploading.
Advanced preview mechanisms have been implemented for each file type: formatted
text display for Word, table parsing for Excel, OCR-based text extraction and alignment
for images, and editable text containers for plain files. Together, these modules
form a cohesive, scalable, and extensible framework for intelligent multilingual document
processing. The result is a technically robust system that demonstrates a
practical balance between automation, user control, and performance optimization
Description
Cataloged from PDF version of thesis.
Includes bibliographical references (page 22).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2026.
Includes bibliographical references (page 22).
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2026.
Keywords
Document translation, Large Language Models (LLMs), Gemini API, Optical Character Recognition (OCR), Web application
