New Approach to Bridging Music and Visual Art through AI-Driven Visual Pattern Christabel Parung (a*), Acep Iwan Saidi (a), Yan Yan Sunarya (a), Wilson Lisan, Krisostomus Nova Rahmanto
a) Bandung Institute of Technology
Abstract
In the area of artistic expression, the interrelationship between music and visual art has has been a matter of debate and discussion among creative thinkers. Nowadays, with Artificial Intelligence (AI) supporting tool, it is possible to create a symbiotic relationship between these two areas. This study proposes a pioneering framework that utilizes the power of AI to bridge the gap between music and visual art through the use of AI-driven visual patterns that can be used in many forms of visual arts.
The aims of this research are 1) to carry out an analysis of the semiotic relationships in musical elements and their visual equivalents (visual elements) 2) to conduct a review of published literature related to the translation of music into visual arts in the last 10 years. By translating the relationship between melody, rhythm, harmony and dynamics as elements of music into visual elements such as line, shape and color, a basic framework will be formed between the two art forms. This framework serves as a link between the abstract language of music and the visual arts.
The methodology used in this qualitative study is a free-drawing experiment on 5 participants as initial data collection, literature review, followed by translating the identified semiotic relationship framework into mathematical formulas to be used in training AI models. This AI model will aim to generate visual patterns based on musical composition. Through semiotic analysis as well as an extensive literature review, this article is able to explore the context of the relationship between music and visual arts, the advancement of AI-generated art, which is based on semiotic analysis.
Keywords: music - visual art - Artificial Intelligence - Visual Pattern
