Wireless voice command system based on Kalman filter and HMM models to control manipulator arm

Abstract

The aim of this work is to implement on real-time a speech recognition module in order to control the movements of a five degree of freedom manipulator arm using a Kalman filter as a selector in noisy environment and HHM model to recognise 12 Arabic spotted words. The methodology adopted is based on detecting and spotting vocabulary words within a phrase generated by user, the system recognises the spotted words using Kalman filter to select these spotted words then a robust HMM (hidden Markov model) technique with cepstral coefficients to improve the recognition rate. To implement the approach on a real-time application, a personal computer parallel port interface was designed to control the movement of a set of stepper motors. The user can control the movements of five degree of freedom (DOF) for a robot arm using a vocal phrase containing spotted words.