Abstract

The main objective of this paper is to implement a real-time speech recognition module to use it in controlling the movements of a five degree of freedom (FOD) manipulator arm using a Kalman filter as a selector in noisy environment and HHM model to recognise 12 Arabic spotted words. The adopted methodology 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 Markove model) technique with cepstral coefficients is used 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.

Key words: Hidden Markove model, kinematics, Kalman filter, recognition, manipulator, robot, degree of freedom, artificial intelligence.