Human Scream Detection and Analysis for Controlling Crime Rate

Crime prevention technologies have become more important in modern urban environments. A human scream can be an early warning sign of danger, distress, or emergency situations. Leveraging machine learning to detect scream-like sounds in real time could enable prompt responses to potential crimes or emergencies. This project will demonstrate how to build a scream detection system using Python and machine learning techniques to automatically identify scream sounds from other non-alert sounds.

This guide is structured for readers who may be new to audio processing and machine learning. It outlines each step in detail, providing a clear path from data preparation to model training and testing.

Table of Contents

1. Introduction to Scream Detection
2. Required Tools and Libraries
3. Data Collection and Preparation
4. Feature Extraction from Audio
5. Model Training
6. Model Evaluation
7. Visualization and Real-Time Testing
8. Building a Simple GUI for Real-Time Prediction
9. FAQs

1. Introduction to Scream Detection