A Simple and Robust Persian Speech Recognition System and Its Application to Robotics

In this paper, a Persian speech recognition system is proposed to recognize Persian isolated spoken words. The main contribution of this work in comparison with the previous ones is simplicity and generality. The proposed system can be widely used in various real world applications when the designer does not need so much expertise in pattern and speech recognition. Due to generality, robustness, computational simplicity and reachability, general frequency domain feature as well as multi-layer percepron neural network as classifier are considered. To demonstrate the efficiency of the proposed speech recognition system, a wheeled mobile robot is navigated in a real domestic environment via Persian spoken commands. The results indicate the high potential of the proposed system to deal with real world applications.