Thesis Abstract

Abstract
The rapid advancements in artificial intelligence (AI) have revolutionized various industries, including music composition and performance. This thesis explores the application of AI in music composition and performance, aiming to enhance creativity and efficiency in the music industry. The study delves into the potential of AI algorithms to compose music autonomously, collaborate with human musicians, and enhance live performances. The research begins with an introduction that outlines the background of the study, identifies the problem statement, and sets the objectives. It also discusses the limitations and scope of the study, emphasizing the significance of integrating AI in the music domain. The structure of the thesis is delineated, providing a roadmap of the subsequent chapters. Chapter two presents a comprehensive literature review on the use of AI in music, covering topics such as machine learning algorithms, neural networks, and generative models. It examines existing AI music composition systems and their impact on creativity, analyzing the benefits and challenges associated with AI-generated music. Chapter three details the research methodology, including data collection methods, software tools, and experimental procedures. It explores how AI algorithms can analyze music data, generate compositions, and adapt to user feedback. The chapter also discusses the evaluation criteria for assessing the quality and creativity of AI-generated music. In chapter four, the findings of the study are discussed in detail, highlighting the capabilities of AI systems in composing music across different genres and styles. The chapter evaluates the effectiveness of AI-generated music in evoking emotions, engaging listeners, and enhancing musical collaboration between humans and machines. Chapter five presents the conclusion and summary of the thesis, emphasizing the implications of integrating AI in music composition and performance. It discusses the future prospects of AI technology in transforming the music industry, fostering innovation, and expanding the creative possibilities for musicians and audiences alike. In conclusion, this thesis underscores the transformative potential of AI in revolutionizing music composition and performance. By leveraging AI algorithms, musicians can explore new creative horizons, collaborate with intelligent systems, and push the boundaries of musical expression. The study contributes to the growing body of research on AI in music, paving the way for a future where technology and art converge to shape the musical landscape.

Thesis Overview