Speaker Recognition System

This code implements a speaker recognition system developed in MATLAB. It utilizes speech signal processing techniques combined with machine learning algorithms to identify different speakers based on their voice characteristics. The program employs feature extraction methods such as MFCC (Mel-Frequency Cepstral Coefficients) and implements classification algorithms like GMM (Gaussian Mixture Models) or SVM (Support Vector Machines) for speaker identification. This system can be applied to various practical scenarios including security authentication, voice-based biometric systems, human-computer interaction interfaces, and speech recognition applications. Furthermore, it serves as a valuable tool for audio processing research and development. The program's architecture allows for continuous optimization through parameter tuning, algorithm improvements, and additional training data to enhance recognition accuracy and overall system performance. The modular design facilitates easy integration of advanced feature extraction techniques and classification models.