This project involves building a real-time audio detection system that continuously listens to system audio, extracts relevant features, and matches them against predefined sound files. When a match is detected, the system identifies and prints the name of the matched sound. The project employs audio processing techniques and machine learning algorithms for feature extraction and comparison, making it suitable for applications such as sound recognition and anomaly detection.