Artificial intelligence in music production: prospects for preparing future masters of musical art for creative activity in a modern professional environment
DOI:
https://doi.org/10.24195/artstudies.2025-3.13Keywords:
artificial intelligence, music production, digital audio workstations (DAW), deep learning models (RNN, VAE, GAN, Transformer), training of future Masters of Musical Art, technological literacyAbstract
The article is devoted to the problems of integrating artificial intelligence (AI) technologies into the digital music production cycle and its significance in the context of professional training of future Masters of Musical Art. The aim of the study is to trace the evolution of AI models from early connectionist and rule-based systems to modern transformer-based architectures, to characterise the factors influencing their applicability in professional workflows for generating musical material, and to determine their advantages and limitations in terms of preparing future Masters of Musical Art for successful creative activity in the modern professional environment.Research methods included retrospective analysis of key stages in the development of AI models, comparative analysis of recurrent neural networks, variational autoencoders, generative adversarial networks, and transformer-based systems, as well as a synthesis of literature using interdisciplinary sources in the fields of computer music, cognitive science, and music pedagogy.The results showed that AI in music production has evolved in line with a sequential process of developing new generations of models: from early symbolic systems to deep generative architectures and multimodal text-to-music conversion technologies. With each stage of model improvement, music producers gained new tools for creativity, but significant limitations and shortcomings that remain to this day necessitate the training of professionals to critically evaluate and adapt generated material integrated into digital audio workstations (DAW). The main prospects for preparing future Masters of Musical Art for creative activity in a modern professional environment are the need to acquire technological literacy, adaptability in working with generated material, and the ability to interact with AI in the format of joint creative and critical awareness of technological and artistic limitations. The prospect for further research is to determine the essence and functions of specific skills of future Masters of Musical Art to successfully engage in creative activity in a modern professional environment, implementing a cycle of music production using AI technologies.
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