Speaker Recognition System Using Vector Quantization (VQ) Method

This program implements speaker recognition using the Vector Quantization (VQ) method, which can be converted to C programming language for efficiency enhancements. VQ is a widely adopted technique in speech processing and voice recognition domains. The system operates by analyzing speaker voice signals, extracting spectral features through techniques like MFCC (Mel-Frequency Cepstral Coefficients), and comparing them against pre-trained speaker models using distance metrics (e.g., Euclidean distance). Key implementation steps include: feature vector clustering via LBG algorithm for codebook generation, and nearest-neighbor classification for speaker matching. The method offers advantages of rapid processing and high accuracy, making it suitable for practical applications. For those interested in speech processing and speaker recognition, converting this program to C language would provide deeper insights into low-level implementation details, memory optimization, and real-time performance tuning in this technical domain.