Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)

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Summarization And Audio Conversion of Video Content

Authors
J. S. V. Sai Hari Priyanka1, *, Y. Lasya Sahithi1, P. Sai Jeswanth1, K. Hema Varshitha1, M. Prem Kumar1
1Department of Information Technology, Anil Neerukonda Institute of Technology and Sciences, Visakhapatnam, Andhra Pradesh, India
*Corresponding author. Email: haripriyanka.it@anits.edu.in
Corresponding Author
J. S. V. Sai Hari Priyanka
Available Online 4 November 2025.
DOI
10.2991/978-94-6463-858-5_192How to use a DOI?
Keywords
Video Summarization; Automatic Speech Recognition (ASR); Natural Language Processing (NLP); Multilingual TTS; Deep Learning
Abstract

The recent growth of video content has made it difficult to quickly summarize useful information. Manual summarizing is slow and infeasible to scale, and traditional approaches may produce unclear summaries and be inferior to deep learning approaches applied to translation or voice synthesis. The proposed framework integrates Automatic Speech Recognition(ASR),Natural Language Processing(NLP), Neural Machine Translation(NMT), and Text-to-Speech(TTS) synthesis to streamline the summarizing process, allowing for a more effective outcome. This model reads the transcription of the video, summarizes it using advanced models, then translates the content to chosen language, and generates high-quality speech output. To evaluate the effectiveness of the model the ROUGE score is used to measure the accuracy of summarization, BLEU score is used to measure the quality of translation across various non-English languages, while the Mean Opinion Score is used to measure the generated speech quality. Experimental results show that the framework did a better job of creating a clear summary, translating language accurately, and producing human-sounding speech, thus recommending this model for individuals with varying language abilities.

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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Volume Title
Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
Series
Advances in Computer Science Research
Publication Date
4 November 2025
ISBN
978-94-6463-858-5
ISSN
2352-538X
DOI
10.2991/978-94-6463-858-5_192How to use a DOI?
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.

Cite this article

risenwbib
TY  - CONF
AU  - J. S. V. Sai Hari Priyanka
AU  - Y. Lasya Sahithi
AU  - P. Sai Jeswanth
AU  - K. Hema Varshitha
AU  - M. Prem Kumar
PY  - 2025
DA  - 2025/11/04
TI  - Summarization And Audio Conversion of Video Content
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 2307
EP  - 2315
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_192
DO  - 10.2991/978-94-6463-858-5_192
ID  - Priyanka2025
ER  -