Using AI for Real-Time Music Composition and Performance

Thesis Abstract

**Thesis Abstract
** The advancement of Artificial Intelligence (AI) has revolutionized various domains, including music composition and performance. This thesis explores the integration of AI technologies in real-time music composition and performance. The primary objective of this study is to investigate the potential of AI algorithms in enhancing creativity and improvisation in musical contexts. By employing AI systems in real-time music creation, this research aims to bridge the gap between human musicianship and technological innovation, ultimately enriching the music production process. The thesis begins with an introduction that provides a comprehensive overview of AI technologies and their applications in the field of music. The background of the study delves into the historical evolution of music composition techniques and the emergence of AI-driven tools in the music industry. The problem statement highlights the limitations of traditional music composition methods and the need for innovative approaches to enhance musical creativity. The objectives of the study are outlined to guide the research process towards achieving the desired outcomes. The literature review chapter critically examines existing research on AI in music composition and performance. Ten key themes are explored, including AI music generation algorithms, machine learning techniques, interactive music systems, and human-AI collaboration in musical contexts. By synthesizing relevant literature, this chapter provides a theoretical framework for understanding the implications of AI technologies in the field of music. The research methodology chapter outlines the approach adopted in this study, including data collection methods, experimental design, and AI model development. Eight key components are discussed, such as data preprocessing techniques, algorithm selection criteria, and evaluation metrics for assessing the performance of AI-generated music compositions. The methodology employed in this research aims to rigorously analyze the impact of AI on real-time music creation and performance. In the discussion of findings chapter, the results of the empirical study are presented and analyzed in detail. The implications of AI-generated music compositions on creativity, expressiveness, and audience engagement are examined. The chapter also explores the challenges and opportunities associated with integrating AI systems into live music performances, highlighting the potential for collaboration between human musicians and AI algorithms. In the conclusion and summary chapter, the key findings of the study are summarized, and the implications for future research and practice are discussed. The significance of this research lies in its contribution to the evolving field of AI-driven music composition and performance, offering new insights into the creative potential of AI technologies in music production. By exploring the intersection of human creativity and machine intelligence, this thesis contributes to the ongoing dialogue on the transformative power of AI in the arts and entertainment industry. Overall, this thesis provides a comprehensive analysis of the use of AI for real-time music composition and performance, offering valuable insights into the potential of AI technologies to enhance musical creativity and innovation. Through empirical research and theoretical exploration, this study advances our understanding of the complex interplay between human musicianship and AI-driven tools in the contemporary music landscape.