MATLAB Implementation of Speech Recognition with Complete Source Code

This is an example of MATLAB source code for speech recognition implementation. The system comprises three main stages: preprocessing, feature extraction, and training/recognition. In the preprocessing stage, the code implements voice signal denoising using techniques like spectral subtraction and signal normalization through amplitude scaling. The feature extraction module includes implementations of Mel-Frequency Cepstral Coefficients (MFCC) and Perceptual Linear Prediction (PLP) feature calculation algorithms, which transform raw audio signals into discriminative feature vectors. Finally, in the training and recognition phase, the code provides classifier implementations including Gaussian Mixture Models (GMM) with expectation-maximization training and Hidden Markov Models (HMM) with Baum-Welch algorithm for parameter estimation. These core components form the essential pipeline for accurate speech content recognition, where each stage can be customized through parameter configuration in the MATLAB code structure.