Designing an AI emotion-based adaptive fuzzy system for evaluation of the computer music

This paper focuses on a design of a template for an AI emotion-based adaptive fuzzy system that analyzes music and simulates the audience's emotional reaction. This system may possibly aid computer music composers in creating music that is more appealing to the wider audiences. Conceptual design of the proposed system is based on the most recent findings in understanding of how the human brain processes musical patterns. This could be summarized in the following statement: any deviation from the musical pattern predictability, in the listener's mind, tend to weaken subsequent pattern anticipation and thereby undercut the impact of further musical deviations. Every single mismatch in musical pattern anticipation is countered by adjustments to the next expectation. When too many deviations fall together, the listener loses track of the underlying musical stability and ceases to anticipate the coming patterns forcefully. With too many deviations, music becomes increasingly incoherent. With too little, music becomes cold and mechanical.