AI Mood-Based Music and Task Recommender System

M.K, SNEHA; DANUSH.V,

doi:https://doi.org/10.55041/ijsmt.v2i4.639

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AI MOOD-BASED MUSIC AND TASK RECOMMENDER SYSTEM

AUTHORS:

SNEHA M.K

DANUSH.V

Mentor

Dr.T.R NISHA DAYANA

Affiliation

DOI: 10.55041/ijsmt.v2i4.639

CC BY 4.0 License:

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Abstract

This paper presents an AI Mood-Based Music and Task Recommender System that intelligently detects user emotions and provides personalized suggestions. The system leverages machine learning, computer vision, and natural language processing techniques to analyze facial expressions, voice tone, and textual inputs. Based on the detected emotional state, it recommends suitable music playlists and productive or relaxing tasks. The system aims to enhance user well-being, reduce stress, and improve productivity. Experimental results show high accuracy in emotion detection and user satisfaction in recommendations.

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This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.

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