Multilingual AI-Based Academic Resource Assistant
DOI:
https://doi.org/10.15662/IJEETR.2026.0802059Keywords:
Multilingual AI Assistant, Academic ResourceRetrieval, FastAPI, Natural Language Processing(NLP), SQLite Database, Language Barriersin Education, Automatic Language Detection, Neural Machine Translation (NMT)Abstract
While digital learning platforms have expanded rapidly, students still struggle to find specific academic resources due to language barriers and unstructured search tools. Most current systems are optimized for English, creating a significant accessibility gap for multilingual learners. To address this, we developed a Multilingual AI-Based Academic Resource Assistant that allows users to search for educational materials in their native language. The system utilizes automatic language detection and neural machine translation to standardize diverse inputs into English for processing. We implemented a rule-based Natural Language Processing (NLP) module for intent detection and used keyword-based extraction to categorize search topics. The backend, built on the FastAPI framework, ensures scalable query handling, while a structured SQLite database provides fast retrieval of relevant materials via optimized SQL queries.Experimental evaluations demonstrate that the assistant accurately classifies user intent and retrieves high-quality resources with minimal latency. By eliminating linguistic obstacles and streamlining the search process, this framework supports a more inclusive digital education environment and offers a scalable solution for academic institutions and online learning platform
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