MUSIC RECOMMENDATION SYSTEM USING FACIAL EXPRESSION RESEARCH

Computer Science and Engineering

Face detection and emotion selection is the one of the current topic in the security field which provides solution to various challenges. Beside traditional challenges in captured facial images under uncontrolled settings such as varying poses, different lighting and expressions for face recognition and different sound frequencies for emotion recognition. For the any face and emotion detection system database is the most important part for the comparison of the face features and sound Mel frequency components. Music is one of the most fruitful media as it can in still deep feelings and marsh listeners with subliminal messages. It skilfully plays with our emotions which in turn influence our mood. Books, movies and television show are a few other means but, in disparity to these, music convey its message in sheer moments. It can aid us when we are feeling low and entrust us. When we listen to sad songs, we tend to feel a downswing in mood. When we listen to happy songs, we feel happier. The sentiment analysis has been explored by several Internet services to endorse contents in line with human emotions, which are expressed through casual texts posted on social network. Music recommendation will mainly work on enhancing user’s mood by providing song by detecting the facial expression of the end user and according to its expression it recommend the preferrable song. This paper extract the human expression and suggest the song according to it and if the user accept that song then the song starts to play.

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