UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 1 | January 2026

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Volume 13 Issue 1
January-2026
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2601162


Registration ID:
574397

Page Number

b429-b436

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Title

Deep Learning-Based Emotion Recognition from Instrumental Hindi Music Signal

Abstract

Music Emotion Recognition (MER) is an important research area within Music Information Retrieval that focuses on automatically identifying emotional characteristics conveyed by music. Although deep learning approaches have shown promising performance, most existing studies rely heavily on vocal or lyrical information and are largely based on Western music datasets. As a result, emotion recognition from instrumental Hindi music remains relatively underexplored. This paper presents a Convolutional Neural Network (CNN)-based framework for emotion recognition using instrumental (voice-removed) Hindi music from the MER500 dataset. Audio signals are converted into spectrogram representations using the Short-Time Fourier Transform and used as input to a CNN for automatic learning of discriminative spectral–temporal features. Experiments are conducted under two configurations: a five-category classification setting (Devotional, Happy, Party, Romantic, and Sad) and a four-category setting obtained by removing the Happy emotion class, which exhibits high ambiguity in instrumental music. The five-category experiment achieves an overall classification accuracy of 64% with a macro-averaged F1-score of 0.64, while excluding the Happy class improves performance to a test accuracy of 67.80% and a macro F1-score of 0.68. The results demonstrate that instrumental Hindi music contains meaningful emotional cues and emphasize the importance of emotion taxonomy design when performing emotion recognition without vocal or lyrical information. This work contributes to culturally diverse MER research and provides a foundation for future multimodal emotion recognition studies.

Key Words

Music Emotion Recognition, Convolutional Neural Network, Instrumental Hindi Music, Deep Learning

Cite This Article

"Deep Learning-Based Emotion Recognition from Instrumental Hindi Music Signal", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.13, Issue 1, page no.b429-b436, January-2026, Available :http://www.jetir.org/papers/JETIR2601162.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Deep Learning-Based Emotion Recognition from Instrumental Hindi Music Signal", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.13, Issue 1, page no. ppb429-b436, January-2026, Available at : http://www.jetir.org/papers/JETIR2601162.pdf

Publication Details

Published Paper ID: JETIR2601162
Registration ID: 574397
Published In: Volume 13 | Issue 1 | Year January-2026
DOI (Digital Object Identifier): https://doi.org/10.56975/jetir.v13i1.574397
Page No: b429-b436
Country: Bhopal, Madhya Pradesh, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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