• Sharwin Bobde
• Shamla Mantri
• Pankaj Agrawal
• Dipti Patil
• Vijay Wadhai

Research aimed towards sentiment analysis has gained popularity with the increase in computational power and rise of Big Data, but a negligible part of it covers music based User Mood Recognition (UMR); most methods stem from social media analytics and Natural Language Processing. This paper elucidates the significance of UMR using audio analysis and music listening behaviour. The underlying relations between music listening behaviour and user’s emotions are described to create a strong case for such research. Various research methodologies for Music Emotion Recognition (MER) have been illustrated, which use variations of neural networks for the problem task. A music based UMR system which uses Music Information Retrieval (MIR) and text analysis has also been described. This paper is a review of basic concepts and real-world implementations that support music based UMR, and acts as a precursor to a cloud based system for music listening behaviour based User Mood Recognition, which is currently under development.

"The Building Blocks of Music based User Mood Recognition: A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.858-863, June-2019, Available :http://www.jetir.org/papers/JETIR1906417.pdf

"The Building Blocks of Music based User Mood Recognition: A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp858-863, June-2019, Available at : http://www.jetir.org/papers/JETIR1906417.pdf