Implementation of an AI Using PyTorch for Sound Localization on a Table

1. Introduction 1.1 Background 1.2 Problem Statement 1.3 Objectives 1.4 Structure of the Thesis 2. Literature Review 2.1 Sound Localization Techniques 2.2 Machine Learning in Sound Processing 2.3 Overview of AI Frameworks 2.4 PyTorch in Audio Applications 3. Methodology 3.1 Research Design 3.2 Data Collection Methods 3.3 Model Architecture 3.4 Training and Evaluation 4. Sound Localization Algorithms 4.1 Basics of Localization Algorithms 4.2 Beamforming Techniques 4.3 Time Difference of Arrival 4.4 Frequency Domain Methods 5. PyTorch Framework Overview 5.1 PyTorch Fundamentals 5.2 Neural Network Modules 5.3 Training Mechanisms 5.4 Model Deployment 6. Implementation Details 6.1 Data Preprocessing 6.2 Model Construction 6.3 Training Process 6.4 Performance Metrics 7. Evaluation and Results 7.1 Experimental Setup 7.2 Quantitative Analysis 7.3 Qualitative Observations 7.4 Comparative Analysis 8. Conclusion 8.1 Summary of Findings 8.2 Contributions to the Field 8.3 Limitations 8.4 Future Work