Thesis Abstract

Abstract
The continuous advancements in artificial intelligence (AI) have revolutionized various industries, including music composition. This research project focuses on the development of an AI Music Composer System using deep learning techniques. The objective of this study is to explore the application of deep learning algorithms in generating musical compositions autonomously. The system aims to analyze existing music data, learn patterns, and create original music compositions based on the learned patterns. Chapter One provides an introduction to the research topic, discussing the background of the study, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definition of terms. The chapter sets the foundation for understanding the significance of developing an AI Music Composer System using deep learning techniques. Chapter Two presents a comprehensive literature review that explores existing research on AI in music composition, deep learning algorithms, and their applications in creative domains. The chapter examines various studies, methodologies, and technologies relevant to the development of an AI Music Composer System. Chapter Three outlines the research methodology employed in this study. It includes the research design, data collection methods, data preprocessing techniques, deep learning model selection, training procedures, and evaluation metrics. The chapter provides insights into the systematic approach taken to develop the AI Music Composer System. Chapter Four delves into the discussion of findings derived from implementing the AI Music Composer System. The chapter analyzes the performance of the system in generating music compositions, evaluates the quality of the generated music, and compares the results with human-composed music. The findings offer valuable insights into the capabilities and limitations of the AI Music Composer System. Chapter Five serves as the conclusion and summary of the project thesis. It consolidates the key findings, discusses the implications of the research outcomes, and suggests future directions for enhancing the AI Music Composer System. The chapter concludes with a reflection on the contributions of this study to the field of AI in music composition and its potential impact on the music industry. In conclusion, the "Development of an AI Music Composer System using Deep Learning Techniques" represents a significant advancement in the field of AI and music composition. By leveraging deep learning algorithms, this research project aims to push the boundaries of creativity and innovation in music production. The findings of this study contribute to the growing body of knowledge on AI-driven music composition and pave the way for further exploration in this exciting domain.

Thesis Overview