VĀṆĪTYĀ - AN INDIC LANGUAGE LEARNING PLATFORM

Vāṇītyā – An Indic Language Learning Platform presents an integrated approach to language education thatleverages advanced machine learning techniques and modern full-stack development to create an adaptive,personalized learning experience. In addressing real-world challenges, Vāṇītyā specifically targets commondifficulties faced by learners of Indic languages, such as mastering the nuances of phonetics and scriptvariations. For instance, learners often struggle with distinguishing subtle differences in vowel sounds—afundamental yet challenging aspect of language acquisition. By dynamically adjusting the frequency anddifficulty of exercises based on user performance, the platform not only reinforces core language skills but alsobuilds confidence and competence over time. This adaptive, data-driven approach demonstrates a significantadvancement in educational technology, offering a scalable solution to overcome the barriers encountered intraditional language learning environments. The platform synergizes a fine-tuned large language model, trainedon over 1.5 million tokens sourced from IndicTrans, with a custom-built reinforcement learning model togenerate, evaluate, and tailor language exercises in real time. This dual-model architecture supports diverselanguage exercises—including transliteration, translation, and interactive quizzes—and seamlessly adapts toindividual user performance

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-05
DOI
https://doi.org/10.5281/zenodo.15158887
Primary Topic
Spider Taxonomy and Behavior Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

VĀṆĪTYĀ - AN INDIC LANGUAGE LEARNING PLATFORM

Zenodo (CERN European Organization for Nuclear Research)
Spider Taxonomy and Behavior Studies
article

VĀṆĪTYĀ - AN INDIC LANGUAGE LEARNING PLATFORM

article en

Abstract

Vāṇītyā – An Indic Language Learning Platform presents an integrated approach to language education thatleverages advanced machine learning techniques and modern full-stack development to create an adaptive,personalized learning experience. In addressing real-world challenges, Vāṇītyā specifically targets commondifficulties faced by learners of Indic languages, such as mastering the nuances of phonetics and scriptvariations. For instance, learners often struggle with distinguishing subtle differences in vowel sounds—afundamental yet challenging aspect of language acquisition. By dynamically adjusting the frequency anddifficulty of exercises based on user performance, the platform not only reinforces core language skills but alsobuilds confidence and competence over time. This adaptive, data-driven approach demonstrates a significantadvancement in educational technology, offering a scalable solution to overcome the barriers encountered intraditional language learning environments. The platform synergizes a fine-tuned large language model, trainedon over 1.5 million tokens sourced from IndicTrans, with a custom-built reinforcement learning model togenerate, evaluate, and tailor language exercises in real time. This dual-model architecture supports diverselanguage exercises—including transliteration, translation, and interactive quizzes—and seamlessly adapts toindividual user performance

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 48%
Spider Taxonomy and Behavior Studies
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