VQ-Based Speaker Recognition System Implementation

Course Design Requirements and Objectives Speech recognition represents a critical component in human-computer interface design and serves as a vital application technology in speech signal processing. Vector Quantization (VQ) has demonstrated excellent performance in isolated word recognition systems, particularly through Finite-State Vector Quantization (FSVQ) techniques that significantly enhance recognition accuracy. VQ-based isolated word recognition systems offer superior comprehensive characteristics including high classification accuracy, minimal storage requirements, and real-time response capabilities. This course project requires designing a speaker-dependent isolated word recognition system using VQ methodology. Utilizing MATLAB tools, students will develop VQ codebook training programs and recognition algorithms to identify specific voice commands such as "Up," "Down," "Left," and "Right." Key implementation components include: 1. Designing a speaker-dependent isolated word recognition system based on VQ technology, encompassing voice acquisition and recognition detection experiments 2. Developing MATLAB simulation programs with system modulation and performance analysis 3. Implementing feature extraction algorithms (e.g., MFCC) and VQ codebook generation using LBG algorithm 4. Creating pattern matching mechanisms through distance calculation functions like Euclidean distance measurement