Implementation of Vector Quantization-Based Speaker Recognition System

This MATLAB-based implementation creates a vector quantization (VQ) driven speaker recognition system capable of real-time identification from 1-7 second voice segments during live recording sessions. The system achieves text-independent automatic speaker verification through the following technical workflow: feature extraction using 12-dimensional MFCC vectors, codebook generation with LBG clustering algorithm, and distance calculation using Euclidean distortion measures between input vectors and stored codebooks. Before operation, users must complete these setup steps: 1. Launch MATLAB software environment 2. Configure the Current Directory to point to the VQ system folder (example: E:\vq) containing essential MATLAB functions (vqtrain.m for training, vqrecognize.m for identification) 3. Execute respective commands in the Command Window: run vqtrain for model generation and vqrecognize for real-time recognition The system significantly enhances speaker verification accuracy and efficiency through optimized codebook design and dynamic time warping compensation. Its modular architecture allows integration with broader speech processing applications, including voice biometrics and security systems, demonstrating substantial potential for cross-domain implementation in audio authentication technologies.