Proceedings of the International Conference on Smart Systems and Social Management (ICSSSM 2025)

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Deep Learning-Based Acoustic Analysis of Assamese Traditional songs with specific reference to Brajavali language present in Borgeet

Authors
Gaurav Narayan Baruah1, Bhagyasri Bora2, Parismita Sarma1, *
1Department of Information Technology, Gauhati University, Guwahati, Assam, India
2Department of Computer Science and Engineering, Central Institute of Technology, Kokrajhar, Assam, India
*Corresponding author. Email: pari@gauhati.ac.in
Corresponding Author
Parismita Sarma
Available Online 29 December 2025.
DOI
10.2991/978-94-6463-950-6_33How to use a DOI?
Keywords
Automated Music Classification; DNNs; CNNs; LSTM models; MFCC feature extraction; Classical Music of India
Abstract

This research presents a comparative study on the classifica- tion of a few Assamese traditional songs, Bihugeet, Kamrupiya Lokogeet, and the devotional song Borgeet, by employing Deep Learning Tech- niques, including DNN (Deep Neural Network), CNN (Convolutional Neural Network), and LSTM (Long Short-Term Memory). Among them, Borgeet is particularly significant as it is written in Brajavali language, a literary dialect that combines Assamese, Maithili, and Sanskrit languages. This makes Borgeet a valuable resource for multilingual study but at the same time development of an Automatic Speech Recognizer for Borgeet becomes challenging due to a lack of resources on digital plat- forms. In this article, a few preliminary experiments are carried out to measure different acoustic parameters of brajavali language along with the evaluation of MFCC values to classify all these geet (songs) using convolutional neural network. The model achieved the highest accuracy 91.95% and 94.95% F1 score in Borgeet.

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 the International Conference on Smart Systems and Social Management (ICSSSM 2025)
Series
Advances in Intelligent Systems Research
Publication Date
29 December 2025
ISBN
978-94-6463-950-6
ISSN
1951-6851
DOI
10.2991/978-94-6463-950-6_33How 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  - Gaurav Narayan Baruah
AU  - Bhagyasri Bora
AU  - Parismita Sarma
PY  - 2025
DA  - 2025/12/29
TI  - Deep Learning-Based Acoustic Analysis of Assamese Traditional songs with specific reference to Brajavali language present in Borgeet
BT  - Proceedings of the International Conference on Smart Systems and Social Management (ICSSSM 2025)
PB  - Atlantis Press
SP  - 500
EP  - 512
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-950-6_33
DO  - 10.2991/978-94-6463-950-6_33
ID  - Baruah2025
ER  -