Speech dynamic time warping based on ant colony optimization algorithm

The dynamic time warping (DTW) depends much on the accuracy of endpoint detection; the recognition time is too long. The ant colony optimization algorithm is presented to solve the dynamic time warping problem. The algorithm is using adaptive evaporation coefficient, a new state transition rule and so on. The simulation results show that the new algorithm has better global search ability, accurateness than the traditional ant colony algorithm and the traditional DTW; it can provide a better performance in the speech recognition rate.