Özet:

Abstract There are extensive studies about music’s impact on human’s emotional state. Humans detect a wide range of emotions from various genres of music, and music plays an integral role in personality development and the treatment of ailments. Music has tremendous effects on human moods and thoughts. Consequently, it impacts cognitive and biological health, and the concept of well-being through music is acquiring traction. In the treatment of depression, music therapy gets witnessed as an addendum to psychoanalysis. Music can enhance intellectual and physical work, study, sports, relaxation, relieve fatigue, and music therapy, among other things. People often get confused while searching for music according to their interests and mood. Individuals usually listen to a particular genre or performer when they are in a certain mood. Music has the ability to control mood, specifically to boost energy, and reduce anxiety. Listening to the correct song at the opportune timing, may help with mental health. As a result, human mood changes and music have an interdependent affinity. In this paper, we aim to develop an application that can understand facial features (Mood and Emotions) and recommend music accordingly using Machine Learning and Deep Learning as tools and algorithms.

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