AI-Powered Music Production: Revolutionizing Contemporary Popular Music

Artificial intelligence (AI) is increasingly impacting various fields, and music production is no exception. While still in its early stages, AI technology has the potential to revolutionize how music is created, particularly in contemporary popular music (CPM). This article explores the development and practical application of AI tools in CPM production, focusing on the unique characteristics of this genre and the implications for AI design.

Contemporary Popular Music (CPM) encompasses a wide range of genres, including post-rock, rap/hip-hop, electronica, and global styles like K-pop and reggaeton. A key feature of CPM is its reliance on recorded sound as the primary mode of transmission, distinguishing it from folk and art music. Technological innovation, cross-cultural influences, and commercial interests also play significant roles in shaping CPM's identity. The integration of studio technology into the creative process is a defining characteristic, blurring the lines between composer, musician, sound engineer, and producer.

AI tools can be applied in various music production contexts, including traditional composition, live performance/improvisation, and in-studio composition. Traditional composition involves creating a symbolic representation of music (e.g., MIDI), while live performance focuses on real-time interaction. In-studio composition, however, centers around the digital audio workstation (DAW), where recording, editing, and mixing are integrated with composition. This article focuses on in-studio composition as it represents a significant shift in how CPM is produced.

Traditional music production followed a linear process: composition → performance → recording → editing → mixing → mastering. However, in-studio composition has disrupted this linearity. Compositional activities are now intertwined with sound editing and design, blurring the roles of different music professionals. The need for traditional music notation has diminished as artists increasingly rely on recorded sounds and MIDI for organizing sonic events. This shift necessitates a re-evaluation of how AI tools are designed for music production.

The traditional view of MIDI as conveying the 'essence' of music and the separation of composition from other production activities are problematic in the context of in-studio composition. Many existing AI music tools are based on piano-roll representations, which may not adequately capture the nuances of CPM genres that heavily rely on electronically designed sounds and samples. Therefore, AI tools need to be designed to handle all types of information that CPM artists work with, particularly audio. This allows artists to condition AI tools on arbitrary material within their DAW projects.

The article highlights collaborations with professional artists in various CPM genres, such as urban, ambient, experimental, and trance. These collaborations involve artists experimenting with AI tools developed by music AI research labs. The experiences and feedback from these artists provide valuable insights into the practical applications of AI tools in real-world music production scenarios. These insights help identify usage patterns, challenges, and areas for improvement in AI music technology.

Based on the analysis and collaborations, the article offers recommendations for developing AI music tools tailored to CPM production. These recommendations emphasize the importance of audio-based processing, flexible control over AI outputs, and seamless integration with existing DAW workflows. The goal is to create AI tools that augment the artist's creative process, rather than replacing it. Validation criteria are also proposed to ensure the effectiveness and relevance of AI tools in CPM production.

AI technology holds immense potential for transforming music production, particularly in contemporary popular music. By understanding the unique characteristics of CPM and addressing the needs of artists working in this genre, AI developers can create tools that empower musicians and unlock new creative possibilities. The future of AI in CPM production lies in fostering collaboration between AI researchers, developers, and artists to build innovative and effective music creation tools.