Published Paper Details:

Music holds a significant role in enriching our lives, serving as a crucial source of entertainment and often providing a therapeutic experience for music enthusiasts and listeners alike. In today's rapidly evolving world of multimedia and technology, we witness the emergence of advanced music players equipped with features such as fast forward, reverse, variable playback speed, local and streaming playback, volume modulation, and genre classification. The inspiration behind this initiative is driven by the desire to streamline the process of creating music playlists, aiming to reduce the manual effort involved. The idea is to automate playlist generation by tapping into the user's emotional state, with the human face playing a pivotal role in revealing one's mood. Through a direct extraction of input from a camera focused on the individual, we aim to harness facial cues as a means of deducing the emotional state. This approach opens up diverse applications, with a primary focus on extracting mood-related information from the input. Once the emotional state is identified, the system can dynamically compile a personalized list of songs that align with the derived mood. This not only eliminates the time-consuming and tedious task of manually segregating or grouping songs into different lists but also facilitates the creation of an appropriate playlist based on an individual's unique emotional features.