MATLAB Code Implementation for Speech Recognition System

This documentation presents a MATLAB-based speech recognition system implementation consisting of three core M-files: HMM, DTW, and Record. The system operates by converting speech signals into digital data and employing model-matching techniques for recognition. The HMM (Hidden Markov Model) module implements probabilistic state transitions to model temporal patterns in speech, typically using Baum-Welch algorithm for training and Viterbi algorithm for decoding. The DTW (Dynamic Time Warping) component handles nonlinear time alignment between input utterances and reference templates through dynamic programming optimization. The Record module provides real-time audio capture functionality using MATLAB's audio input interfaces, enabling sample acquisition for both training and testing phases. Additional functionalities include model training through iterative parameter estimation and speech synthesis capabilities for waveform generation. The system demonstrates significant practical value with applications spanning speech recognition, voice synthesis, and speaker identification, offering substantial convenience for both daily life and professional workflows.