• Arfia Imtiyaz Shaikh
• Shrimayee Sanjay Mishra
• Saakshi Mayur Raut
• Iffat Kazi

Can music’s emotional essence be captured and visualized computationally? Music has long been associated with human emotions, evoking deep feelings across different cultures and contexts. This paper presents a Music Emotion Visualizer, a system designed to analyze and map the emotional content of music using computational techniques. By processing various audio features such as timbre, rhythm, and harmony, the system predicts emotions in real-time and visualizes them in a emotional radar defined by valence, energy, and tension. The research employs machine learning methodologies, with Partial Least Squares Regression (PLS) as the primary predictive model, demonstrating a high degree of accuracy in classifying emotional states. The system utilizes advanced audio feature extraction techniques to break down the musical composition into measurable attributes, which are then analyzed for emotional cues. The output provides a real-time visualization that enhances the user’s listening experience by revealing the underlying emotional trajectory of a song. This innovative approach has significant implications for various applications, including music recommendation systems, therapy, and creative industries. By offering an intuitive and interactive way to experience music’s emotional impact, this research paves the way for deeper exploration into music perception and affective computing. Future enhancements aim to refine accuracy, expand dataset diversity, and integrate real-time streaming capabilities.

Music Emotion Recognition, Audio Feature Extraction, Machine Learning, Valence, Energy, Tension, Emotion Prediction, Music Information Retrieval, Music Psychology, Sentiment Analysis, Sound Processing, Feature Engineering, Interactive Interface, Computational Musicology.

"Music Emotion Visualizer: A Computational Approach to Mapping Emotions in Music", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.c1-c5, March-2025, Available :http://www.jetir.org/papers/JETIR2503201.pdf

"Music Emotion Visualizer: A Computational Approach to Mapping Emotions in Music", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppc1-c5, March-2025, Available at : http://www.jetir.org/papers/JETIR2503201.pdf