EMOTION-BASED MUSIC RECOMMENDATION SYSTEM

Abstract

Abstract: Music plays a very important role in enhancing an individual’s life as it is an important medium of entertainment for music lovers and listeners and sometimes even imparts a therapeutic approach. In today’s world, with ever increasing advancements in the field of multimedia and technology, various music players have been developed with features like fast forward, reverse, variable playback speed (seek & time compression) local playback, streaming playback with multicast streams and including volume modulation, genre classification etc.The motivation of this work comes from the possibility of reducing the human effort in creating music playlists manually, thus generating them automatically based on the user’s emotional state. The human face plays an important role in knowing an individual's mood. The required input is extracted from the human face directly using a camera. One of the applications of this input can be for extracting the information to deduce the mood of an individual. This data can then be used to get a list of songs that comply with the “mood” derived from the input provided earlier. This eliminates the time-consuming and tedious task of manually Segregating or grouping songs into different lists and helps in generating an appropriate playlist based on an individual's emotional features.