Fuzzy Neural Network In The Music Recognition Application

Music recognition is a rising interdisciplinary research field, which involves physics, signal processing, human-computer interaction, music theory and music psychics. The goal of this recognition is to extract the music characters by audio signal processing and feature selection so that they can be used in music analysis, classification and automatic score recording. To describe piano music characters by computer, this dissertation combines the technique of multimedia, signal processing and pattern recognition with music theory to make the computer to imitate the piano performance evaluation of human.The work in this paper belongs to the research field of music identification theory and its application. Employing audio signal analysis and processing, we make it possible for computer to recognize music characters and evaluate its performance.We firstly outline the conception and framework of automatic piano performance evaluation system based on music recognition theory. The evaluation system is then implemented with performance testing in this paper. Based on music theory and the notes physical attributes, we propose seven music features for identification. Based on music feature selection, the system is able to evaluate the piano playing performance by scores and visualization.The automatic piano performance evaluation system well synthesizes the knowledge in both music and technology areas, making it possible for computers to evaluate music performance automatically. Intelligent music recognition will help the mobile music recognition, music Fountain recognition and music teaching and learning, etc.