A Survey on Exploring the Relationship Between Music and Mental Health Using Machine Learning Analysis

Abstract

This chapter embarks on a journey to probe the intricate relationship between music and mental health through the lens of machine learning algorithms. Acknowledging music's profound influence on emotions and moods, the study delves into its potential therapeutic role for individuals grappling with mental health issues. Capitalizing on the advancements in machine learning, this endeavour endeavours to unveil hidden patterns, correlations, and even causal connections between distinct musical attributes and mental health outcomes. The research methodology charted involves the assimilation of a diverse dataset of music tracks and mental health indicators sourced from participants. Leveraging audio signal processing techniques, pertinent musical features such as tempo, rhythm, pitch, and emotional valence will be extracted. This trove of data will then be subjected to an array of machine learning.