Speech Recognition Using DTW Method

Resource Overview

A speech recognition program implementing the DTW algorithm for isolated digit recognition, featuring dynamic time warping for improved accuracy in temporal pattern matching.

Detailed Documentation

This speech recognition program utilizes the Dynamic Time Warping (DTW) method, which enables more accurate recognition of isolated digits through optimal alignment of time-series data. The implementation involves calculating the minimum warping path between input speech patterns and reference templates using dynamic programming. Currently focused on simple digit recognition, the system employs feature extraction (typically MFCC coefficients) and template matching with distance minimization. We are actively exploring enhancements to handle more complex speech patterns through improved feature vectors and adaptive thresholding. Continuous optimization efforts include refining the DTW distance calculation and incorporating noise robustness techniques. Future developments will expand functionality to support broader vocabulary recognition while maintaining computational efficiency through optimized path constraint strategies.