MATLAB Code Implementation for Voice Recognition

This is a MATLAB-based voice recognition program that can accurately identify different speakers' voices with broad application potential. The implementation typically involves several key stages: signal preprocessing using functions like 'audioread' for input and 'resample' for standardization, feature extraction using Mel-Frequency Cepstral Coefficients (MFCC) through algorithms like 'mfcc' for characteristic vocal patterns, and pattern classification employing machine learning models such as Gaussian Mixture Models (GMM) or Deep Neural Networks (DNN) with MATLAB's Classification Learner toolbox. The program analyzes and processes audio signals using advanced algorithms to identify both speaker identity and speech content. It can serve as a valuable tool for voice recognition research and development, with practical applications in voice-controlled systems, virtual assistants, and voice command interfaces. The robust functionality of this implementation helps users better understand and apply voice recognition technology, featuring modular code structure that allows customization of parameters like frame size, overlap length, and feature dimensions for optimized performance.