A Simple Speaker Recognition System with MATLAB Implementation

This program implements a simple speaker recognition system designed and developed using MATLAB. The core architecture consists of three main modules: speech signal input management module, feature extraction module for speech discrimination, and speaker authentication module. The system employs MFCC algorithm for feature vector extraction from voice samples, which captures vocal tract characteristics through Fourier transform and Mel-scale filtering. The recognition process utilizes pattern matching techniques comparing extracted features against pre-trained speaker models stored in the database. Additional supporting modules include error handling mechanisms for invalid inputs and exception management, along with a GUI (Graphical User Interface) module that provides intuitive waveform visualization and result display. The system accepts voice signal inputs through microphone recording or audio files, processes them through frame blocking and windowing, then performs endpoint detection before feature analysis. This comprehensive implementation supports speaker verification applications like voiceprint identification, contributing to both research and practical applications in speech recognition technology. The modular design allows easy integration of alternative algorithms such as VQ (Vector Quantization) or HMM (Hidden Markov Models) for enhanced performance.