AI-Driven Fusion Framework for Smart Learning Applications

DOI

10.2991/978-94-6463-978-0_40How to use a DOI?

Keywords

Smart Learning; Speech-to-Text; Sub-Intent Classification

Abstract

A Fusion Framework power-driven by intelligent technologies, designed for personalized and smart learning with multimedia capabilities aims to overcome the limitations of conventional one-size-fits-all educational models. It uses Audiotext Net for precise speech recognition, a next-generation intent recognition module, and Sub-Intent-Net to classify sub-intents accurately. These components enable rich, context-aware user interactions and adaptive and immersive learning experiences. The introduced system utilized many of the newest profound learning advancements, such as high-order ConvNet, Bi-GRU network, and BERT-based embedding to attain robust STT, intent classifier, and sub-intent classifier. We plan to extend the framework for multi-lingual communication, for emotion detection, and to deploy it on embedded devices to ensure access to global learning contexts.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jyothi Reddy
AU  - Amjan Shaik
PY  - 2025
DA  - 2025/12/31
TI  - AI-Driven Fusion Framework for Smart Learning Applications
BT  - Proceedings of the 1st Engineering Data Analytics and Management Conference (EAMCON 2025)
PB  - Atlantis Press
SP  - 462
EP  - 472
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-978-0_40
DO  - 10.2991/978-94-6463-978-0_40
ID  - Reddy2025
ER  -