Automatic Mood Classification Model for Indian Popular Music

Music shares a very special relation with human emotions. We often choose to listen to a song or music which best fits our mood at that instant. A lot of research and study has been going on in the field of Music mood recognition in the recent years. We contribute to make an effort for automatic identification of mood underlying the audio songs by mining their spectral and temporal audio features. Our current work involves analysis of various classification algorithms in order to learn, train and test the model representing the moods of the audio songs. The focus is on the Indian popular music pieces and our work continues to analyze, develop and improve the algorithms to produce a system to recognize the mood category of the audio files automatically. The experimental results show a satisfactory performance of the system in recognizing the music mood by using ensemble classification tree techniques.