MATLAB-Based DTW Model Algorithm and Efficient Implementation for Speech Recognition

This project provides a comprehensive MATLAB implementation of the Dynamic Time Warping (DTW) algorithm with optimized computational efficiency. The system performs rapid recognition of spoken digits 0-9 through spectral feature matching. The core algorithm employs dynamic programming to calculate optimal alignment paths between input sequences and reference templates, utilizing Euclidean distance metrics with boundary constraints. Key implementation features include precomputed reference templates for each digit, matrix initialization with infinity padding, and recursive path cost minimization. The testdtw.m script automates the entire workflow from feature extraction to classification decision, incorporating voice activity detection and endpoint detection preprocessing. This DTW implementation demonstrates exceptional effectiveness in achieving accurate digit identification within minimal processing time, making it ideal for embedded speech recognition applications and pattern matching tasks.