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September 10, 2025Deleted Journal

Recognition of Emotions in Music Using Machine Learning Algorithms

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Analysis classifies emotions in Hindi songs, suggesting machine learning can enhance music applications.

XGBoost classifier achieved 86.4% accuracy in identifying emotions from Hindi music clips.
Acoustic features like MFCCs and chroma vectors were extracted from 20-second audio samples for analysis.
Data segmentation used stratified sampling to split into training, validation, and testing sets.
Results imply effective emotion classification can enhance mood-based music applications, like playlists.

Shelke et al. (2025) studied this question.

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September 10, 2025Deleted Journal

View Full Paper

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Authors

Analysis classifies emotions in Hindi songs, suggesting machine learning can enhance music applications.

XGBoost classifier achieved 86.4% accuracy in identifying emotions from Hindi music clips.
Acoustic features like MFCCs and chroma vectors were extracted from 20-second audio samples for analysis.
Data segmentation used stratified sampling to split into training, validation, and testing sets.
Results imply effective emotion classification can enhance mood-based music applications, like playlists.

Shelke et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark