Design of an English Speaking Interactive System Based on Artificial Intelligence

In order to improve the human-machine interaction effect of current English service robots, the author proposes an English intelligent dialogue human-machine interaction system using speech recognition as the basic method. By optimizing the feature parameter extraction method and speech recognition model of the interaction system, combined with corresponding module design, the performance of the interaction system has been improved to a certain extent. The simulation results show that compared with other feature parameter extraction algorithms, the LPMFCC feature parameter extraction algorithm in this study has a higher recognition rate of 87.4%; Compared with the pre improved HMM model, the improved HMM model proposed by the author can complete training faster and with lower training errors, requiring only 4 training sessions to complete the training. Conclusion: The results indicate that the English intelligent dialogue human-machine interaction system proposed by the author can achieve good performance and achieve good human-machine interaction effects, which has certain reference value for practical design.