Volume 1 Issue 2
ANALYSIS OF VOICE RECOGNITION ALGORITHMS IN ELECTRONIC SYSTEM USING MATLAB
Voice recognition has become one of the most important tools of the modern generation and is widely used in various fields for various purposes. The past decade has seen dramatic progress in voice recognition technology, to the extent that systems and high-performance algorithms have become accessible. Voice recognition system performance is commonly specified in terms of speed and accuracy, recognition accuracy is the most important and straightforward measure of voice recognition performance. This research were proposed to review several voice algorithms in terms of detection accuracy and processing overhead and to identify the optimal voice recognition algorithm that can give the best trade-offs between processing cost (speed, power) and accuracy. Also, to implement and verify the chosen voice recognition algorithm using MATLAB. Ten words were spoken in an isolated way by male and female speakers (four speakers) using MATLAB as a simulation environment, these word were used as a reference signal to trained the algorithm, for evaluating phase, all algorithms dictates to subject them to similar test criteria. From the simulation results, the Wiener Filter algorithm outperform the other four algorithms in terms of all measure of performance, and power requirement with the moderate complexity of the algorithm and its prospective implementation as a hardware. Wiener filter algorithm scored accuracy of 100%, 5%, and 50% for test cases i,ii,and iii respectively, with recognition speed range of (695-867) msec and estimated power range of (750-885) µW.
— voice recognition, spectrum normalization, cross-correlation, auto- correlation , wiener filter , hidden markov model, Matlab.