Mode Recognition of Chinese National Music Using Machine Learning for Intelligent Electronic Music Systems

This paper proposes an intelligent mode recognition framework for Chinese national music by integrating traditional music theory with machine learning techniques tailored for electronic music systems. The framework constructs a mode template based on characteristic pitch structures extracted from MIDI-formatted melodies. The recognition process begins with melodic feature analysis to determine tonality, followed by the extraction and classification of chord features into generalized triadic structures. A fuzzy reasoning mechanism is employed to compute chord energy scores and generate candidate chord progressions. Subsequently, the system conducts an unbiased tonal evaluation and matches the input to predefined mode templates to identify the musical mode. Experimental results confirm the framework’s effectiveness in accurately recognizing both pentatonic and heptatonic modes. Designed for electronic compatibility, the proposed system is well-suited for applications in intelligent musical instruments, IoT-enabled audio analysis devices, and AI-driven digital composition platforms.