The ASR Approach Based on Embedded System for Meal Service Robot

This paper presents to apply Automatic Speech Recognition (ASR) algorithm to the meal service robot so that the user can be easier to order the meal and increase interaction between the robot and human. The Mel-frequency Cepstral coefficients (MFCC) is used to scratch the feature parameters, and Hidden Markov Model (HMM) is applied as the recognition speech model via Spce3200. It is based on the embedded HMM for speech recognition and thus reducing the size and power in a less computational time. There are 25 sets of Chinese speech data are trained and tested using a sentence and multi sentences under different environments. The highest recognition rate in a sentence has confirmed up to 95%, and multi-sentences can reach 85%. Accordingly, the practical results have indicated its relevant reliability.