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Introduction

Natural language generation (NLG) is a subfield of artificial intelligence that focuses on the automatic generation of human-like text. NLG has found applications in various domains such as chatbots, summarization, and machine translation. One emerging area of research within NLG is automated storytelling, where researchers aim to develop systems that can automatically generate narrative texts. This thesis explores the use of NLG for automated storytelling and investigates the challenges and opportunities in this field.

1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of Terms

Chapter 2: Literature Review
2.1 Introduction to NLG
2.2 Automated Storytelling
2.3 NLG Techniques for Story Generation
2.4 Evaluation Metrics for NLG Systems
2.5 Applications of NLG in Storytelling
2.6 Challenges in NLG for Storytelling
2.7 Previous Studies on NLG for Storytelling
2.8 Emerging Trends in NLG for Storytelling
2.9 Summary of Literature Review
2.10 Research Gap

Chapter 3: System Design and Methodology
3.1 Introduction to System Design
3.2 Data Collection for NLG Model
3.3 Preprocessing of Data
3.4 NLG Model Selection
3.5 Training and Testing of NLG Model
3.6 Evaluation of NLG Model
3.7 User Testing and Feedback
3.8 Refinement of NLG Model
3.9 Summary of System Design and Methodology

Chapter 4: System Implementation
4.1 Introduction to System Implementation
4.2 Setting Up NLG Environment
4.3 Developing NLG Model
4.4 Integrating NLG Model with Storytelling Platform
4.5 Testing and Debugging NLG System
4.6 User Interface Design
4.7 Performance Optimization
4.8 System Deployment
4.9 Summary of System Implementation

Chapter 5: Conclusion and Summary
5.1 Summary of Findings
5.2 Contributions of the Study
5.3 Future Directions
5.4 Conclusion

Thesis Overview

Natural language generation (NLG) for automated storytelling is a growing field within artificial intelligence that aims to develop systems capable of generating narrative texts automatically. This thesis explores the use of NLG techniques for automated storytelling and investigates the challenges and opportunities in this area.

Chapter 1 provides an introduction to the research topic, background information, problem statement, objective, limitations, scope, significance of the study, structure of the thesis, and definition of terms related to NLG for automated storytelling.

Chapter 2 presents a comprehensive literature review on NLG techniques, automated storytelling, evaluation metrics, applications, challenges, previous studies, emerging trends, and research gaps in the field.

Chapter 3 discusses the system design and methodology involved in developing an NLG system for automated storytelling, including data collection, preprocessing, model selection, training, testing, evaluation, user testing, and refinement.

Chapter 4 provides detailed information on the system implementation process, covering setting up the NLG environment, developing the NLG model, integrating it with a storytelling platform, testing, debugging, user interface design, performance optimization, and system deployment.

Chapter 5 concludes the thesis with a summary of findings, contributions of the study, future directions for research, and a final conclusion on the use of NLG for automated storytelling. This thesis aims to contribute to the growing body of knowledge in NLG research and provide insights into the potential applications of NLG in storytelling.

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