Speech Recognition using Dynamic Time Warping

Abstract

Speech Recognition is a technology enabling human interaction with machines. The design of a speech recognition system capable of 100% accuracy is far from solved. This paper describes an isolated word, speaker dependent speech recognition system capable of recognizing spoken words at sufficiently high accuracy. The system has been tested and verified on MATLAB as well as the TMS320 C6713 DSK with an overall accuracy exceeding 90%. The paper shows the memory efficiency offered by using speech detection for separating the words from silence and the improved system performance achieved by using Dynamic Time Warping while keeping in view the overall design process, supported by experimental results. In future, speech recognition can serve as a means of data interoperability and distribution by allowing a mobile user (client) to retrieve information from the data networks (GPRS, WEB) using a client server architecture. The satellite system can be used as a wireless medium for accessing the data network.