Speech recognition based microcontroller for wheelchair movement

Abstract EN

This paper introduced an approach to design and implement a control system for the movement of wheelchair by means of the human voice for paralyzed patients.

In this paper, the Mel-Frequency Cepstral Coefficient (MFCC) technique is used as feature extraction with Dynamic Time Warping (DTW) for features matching.

The output of the system is used to control the movement of the wheelchair through an interface between notebook and microcontroller.

The experimental results showed that the proposed methods gave a recognition rate 100% of the already trained speakers with environment noise reach to 66dB.

The test was conducted at different sound levels of the surrounding environment (53 to 73) dB as measured by Sound Level Meter (SLM).