Design and Implementation of Music Composition Aid System Based on Artificial Intelligence

Abstract

In an era marked by the convergence of technology and artistic expression, the field of music composition stands at the forefront of innovation, offering a fertile ground for the exploration of Artificial Intelligence (AI) as a creative tool. This study presents the design and implementation of a Music Composition Aid System driven by AI, with a focus on leveraging the Variational Autoencoders (VAEs) algorithm. Through meticulous experimentation and evaluation, they examine the system's performance in generating musical compositions, assessing metrics such as accuracy, diversity, novelty, and fluency. The findings demonstrate the system's ability to produce compositions that closely emulate human-authored works while offering novel and innovative musical ideas. Furthermore, qualitative assessments through expert evaluations and user feedback highlight the system's capacity to inspire creativity and facilitate experimentation in music composition. By bridging the gap between technology and creativity, this study offers insights into the transformative potential of AI in reshaping the landscape of musical expression and innovation.