Authors :
Likith P; Sahana N D; Puneeth P; Niranthar M; Aruna M G
Volume/Issue :
Volume 9 - 2024, Issue 9 - September
Google Scholar :
https://tinyurl.com/yj54nnkm
Scribd :
https://tinyurl.com/4bje9t6s
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24SEP1335
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
In modern educational settings, ensuring that
all students effectively comprehend lecture content is a
significant challenge, particularly when language barriers
and varying levels of cognitive processing ability come
into play. Traditional classroom instruction often fails to
accommodate the diverse needs of all learners, leading to
gaps in understanding and academic performance. This
research explores the implementation of a real-time audio
transcription system as a solution to enhance classroom
inclusivity and comprehension. By leveraging mobile
technology, students can access live speech-to-text
transcriptions of lectures directly on their devices. This
system is designed to assist students who struggle with
listening due to language differences, hearing
impairments, or other cognitive challenges.
The study delves into the technological framework of
the transcription service, evaluating its accuracy, latency,
and usability. It also considers the practical implications
of integrating such technology into various classroom
settings, from elementary schools to higher education
institutions. Through surveys and interviews with
students and teachers, the research assesses the impact of
live transcription on student engagement, participation,
and academic performance. Preliminary findings suggest
that live audio transcription can significantly bridge the
comprehension gap, offering a practical tool to foster a
more inclusive and effective learning environment.
Additionally, the study explores potential challenges and
solutions for widespread implementation, aiming to
provide a comprehensive analysis of the benefits and
limitations of this innovative educational tool.
References :
- Text to Speech Conversion using Raspberry - PI Vinaya Phutak, Richa Kamble, Sharmila Gore, Minal Alave, R.R.Kulkarni Department of Electronics and Telecom- munication Engineering
- “Internet of things applications using Raspberry-Pi: asurveyKhalid M. Hosny1, Amal Magdi1, Ahmad Salah2, Osama El-Komy1,Nabil A. Lashin11Department of Infor- mation Technology, Zagazig University, Zagazig, Egypt 2Department of Computer Science, Zagazig University, Zagazig, Egypt.
- IoT Application Development Based on Java and Raspberry Pi by Zheng Lu and Xing Liu, 2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON).
- Vietnamese Voice2Text: A Web Application for Whisper Implementation in Vietnamese Automatic Speech Recognition Tasks” by Quangphuoc Nguyen, Ngocminh Nguyen, Thanhluan Dang, and Vanha Tran.
- The implementation of Speech to Text Conversion Using Hidden Markov Model by A. Elakkiya, K. Jaya Surya, Konduru Venkatesh, and S. Aakash.
- The Developing of the System for Automatic Audio to Text Conversion Oleh Basystiuk, Natalya Shakhovska, Violetta Bilynska, Oleksij Syvokon, Oleksii Shamuratov, Volodymyr Kuchkovskiy.
- Self-Supervised Audio-and-Text Pre-training with Extremely Low-Resource Parallel Data Authors Yu Kang TAL Education Group, Tianqiao Liu TAL Education Group, Hang Li TAL Education Group, Yang Hao TAL Education Group, Wenbiao Ding TAL Education Group, Tencent.
- Different Methods Review for Speech to Text and Text to Speech Conversion by Deep Kothadiya Post Graduate Student MIT, Nitin Pise, PhD Professor MIT, Mangesh Bedekar Professor MIT, International Journal of Computer Applications September 2020.
- Speech to Text Translation Enabling Multilingualism by Shahana Bano, Pavuluri Jithendra, Gorsa Lakshmi Niharika and Yalavarthi Sikhi - Department Of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, India - 2020 IEEE International Conference for Innovation in Technology (INOCON).
In modern educational settings, ensuring that
all students effectively comprehend lecture content is a
significant challenge, particularly when language barriers
and varying levels of cognitive processing ability come
into play. Traditional classroom instruction often fails to
accommodate the diverse needs of all learners, leading to
gaps in understanding and academic performance. This
research explores the implementation of a real-time audio
transcription system as a solution to enhance classroom
inclusivity and comprehension. By leveraging mobile
technology, students can access live speech-to-text
transcriptions of lectures directly on their devices. This
system is designed to assist students who struggle with
listening due to language differences, hearing
impairments, or other cognitive challenges.
The study delves into the technological framework of
the transcription service, evaluating its accuracy, latency,
and usability. It also considers the practical implications
of integrating such technology into various classroom
settings, from elementary schools to higher education
institutions. Through surveys and interviews with
students and teachers, the research assesses the impact of
live transcription on student engagement, participation,
and academic performance. Preliminary findings suggest
that live audio transcription can significantly bridge the
comprehension gap, offering a practical tool to foster a
more inclusive and effective learning environment.
Additionally, the study explores potential challenges and
solutions for widespread implementation, aiming to
provide a comprehensive analysis of the benefits and
limitations of this innovative educational tool.