Voice Recognition Algorithm for Portable Assistive Devices

We present here the implementation of a robust voice recognition algorithm for voice activated control of assistive devices. We implemented an effective method based on cross correlation of Mel Frequency Cepstral Coefficients (MFCC). The developed method yields high accuracy in low noise environment. Because our implementation is based on a set of training samples for each command, it can be easily adapted for any user. Once the training set is loaded, every command is compared to the MFCCs of all samples in the training set. We then use a "winner-takes-all" method to decide which group the command belongs to.