Dynamic Time Warping Algorithm for Speech Recognition

This MATLAB implementation of the Dynamic Time Warping (DTW) algorithm includes comprehensive test programs for speech recognition applications. The DTW algorithm serves as a crucial technique for speech recognition by comparing input speech signals with pre-established templates to identify spoken words or phrases. As a time-series matching algorithm, DTW effectively addresses temporal misalignments in speech signals caused by varying speaking rates, making it particularly valuable for handling time-warping issues in audio data. The implementation typically involves key functions for feature extraction (such as MFCC computation), distance matrix calculation using Euclidean or other metrics, and optimal path finding through dynamic programming. In the field of speech recognition, DTW finds extensive applications in both recognition systems and speech synthesis technologies. The MATLAB-based implementation allows researchers to conduct experiments and performance tests, facilitating improvements in recognition accuracy and system efficiency through parameter optimization and algorithm enhancements.