Classification of Music Genre Using Deep Learning Approaches

Music genre classification is a pivotal area of research within audio technology, holding immense importance for content organization and recommendation. Audio feature extraction and Music genre classification constitute a complete recognition system. Audio feature analysis and Music genre classification together form an integrated recognition system for comprehensive music genre identification and organization. This technology is frequently utilized to accurately detect and classify various types of music genres or characteristics present in audio signals, contributing significantly to the effective organization and recommendation of music content. Our experiment was conducted with the dataset from GTZAN that is taken from Kaggle repository. Convolutional neural networks (CNN) are employed to train our model, which is subsequently utilized for the classification of music genres in audio signals.

Authors

Publication Details

Published
2024-10-26
DOI
https://doi.org/10.1109/aisp61711.2024.10870721
Primary Topic
Music and Audio Processing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Classification of Music Genre Using Deep Learning Approaches

T. Manohar, Umamahesh Srinivas, M. Venkateswara Rao, Shaik Rafi
Music and Audio Processing
article

Classification of Music Genre Using Deep Learning Approaches

T. Manohar, Umamahesh Srinivas, M. Venkateswara Rao, Shaik Rafi
article en

Abstract

Music genre classification is a pivotal area of research within audio technology, holding immense importance for content organization and recommendation. Audio feature extraction and Music genre classification constitute a complete recognition system. Audio feature analysis and Music genre classification together form an integrated recognition system for comprehensive music genre identification and organization. This technology is frequently utilized to accurately detect and classify various types of music genres or characteristics present in audio signals, contributing significantly to the effective organization and recommendation of music content. Our experiment was conducted with the dataset from GTZAN that is taken from Kaggle repository. Convolutional neural networks (CNN) are employed to train our model, which is subsequently utilized for the classification of music genres in audio signals.

Openalex Percentile: Top 70%
Music and Audio Processing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.