Investigating the Impact of Neural Networks on Modern Text-to-Speech Technology Development

1. Introduction 1.1 Background 1.2 Objectives of the Study 1.3 Research Questions 1.4 Structure of the Thesis 2. Overview of Text-to-Speech Technology 2.1 Historical Development 2.2 Key Concepts and Terminologies 2.3 Current State of TTS Technology 3. Fundamentals of Neural Networks 3.1 Basic Principles 3.2 Types of Neural Networks 3.3 Training and Optimization 4. Integration of Neural Networks in TTS 4.1 Neural Networks in Speech Synthesis 4.2 Key Algorithms and Frameworks 4.3 Challenges in Implementation 5. Case Studies of Neural-Based TTS Systems 5.1 Google's Tacotron 5.2 DeepMind's WaveNet 5.3 Other Notable Systems 6. Impact Assessment on TTS Development 6.1 Performance Improvements 6.2 Quality of Speech Output 6.3 Scalability and Flexibility 7. Comparative Analysis 7.1 Traditional vs Neural Network Approaches 7.2 Evaluation Metrics 7.3 User Experience and Feedback 8. Conclusion and Future Directions 8.1 Summary of Findings 8.2 Implications for TTS Technology 8.3 Recommendations for Future Research