MATLAB Implementation for Male and Female Voice Recognition

In this documentation, I present modifications to the male and female voice recognition program, which constitutes the second assignment for the Digital Signal Processing course at Chinese Academy of Sciences. The implementation focuses on enhancing recognition resolution to exceed 90% accuracy through improved feature extraction algorithms and machine learning classification techniques. Key technical enhancements include: - Implementation of MFCC (Mel-Frequency Cepstral Coefficients) for robust acoustic feature extraction - Integration of SVM (Support Vector Machine) or GMM (Gaussian Mixture Model) classifiers for gender classification - Development of an intuitive GUI using MATLAB's App Designer or Guide for seamless user interaction The program builds upon existing foundation code with significant improvements in signal preprocessing, including voice activity detection and noise reduction algorithms. The modified code ensures reliable performance through comprehensive testing and validation procedures. Should you encounter any operational issues during implementation or execution, please feel free to contact me for technical assistance and code troubleshooting support.