Voice Operated Wheelchair for Physically Disabled

Abstract

A conventional wheel chair is manually operated and always requires a person to carry the disabled, considering this drawback we brought the idea of a wheel chair which is controlled by using speech signal. This solves the problem of relying on others for ones movement. In the voice operated wheel chair the input speech signal is given through micro phone. Speech extractor is used to convert the given speech signal to word signal. The extracted word signal is recognized by using the speech recognizer. The word signal generates the command. According to the generated command the various operations were performed in the mobile robot like move forward, backward, left and right, clockwise rotate, anticlockwise rotate, open, close, up, down, and stop. The methods used in this research are Linear Predictive Coding (LPC) and Hidden Markow Model (HMM).LPC is used to extract word data from speech signal. HMM is used to recognize the word pattern data, which are extracted from a speech signal .Sampling rate of the speech signal is 8kHz.The use of intelligent wheelchair encourages the view of the machine as a partner rather than as a tool. These people, suffering from disorientation, amnesia, or cognitive deficits, are dependent upon others to push them, so often feel powerless and out of control. Intelligent wheelchair has the potential to provide these people with effective ways to alleviate the impact of their limitations.