Speech Recognition Using Linear Predictive Coding and Artificial Neural Network for Controlling Movement of Mobile Robot

摘要

This paper describes about implementation of speech recognition system on a mobile robot for controlling movement of the robot. The methods used for speech recognition system are Linear Predictive Coding (LPC) and Artificial Neural Network (ANN). LPC method is used for extracting feature of a voice signal and ANN is used as the recognition method. Backpropagation method is used to train the ANN. Voice signals are sampled directly from the microphone and then they are processed using LPC method for extracting the features of voice signal. For each voice signal, LPC method produces 576 data. Then, these data become the input of the ANN. The ANN was trained by using 210 data training. This data training includes the pronunciation of the seven words used as the command, which are created from 30 different people. Experimental results show that the highest recognition rate that can be achieved by this system is 91.4%. This result is obtained by using 25 samples per word, 1 hidden layer, 5 neurons for each hidden layer, and learning rate 0.1.