Vehicle Intelligent Control System Based on Voiceprint Recognition

As the most widely applied intelligent system in vehicles, the stability and accuracy of speech recognition results are crucial for voice-controlled systems. This paper first employs microphone array source localization technology and speech detection to achieve multi-input speech separation, reducing unnecessary judgments. Secondly, speech recognition results with confidence levels are obtained through voiceprint recognition technology. Finally, a dynamically adjustable decision module produces corrected speech recognition results. In the dynamic decision module, self-learning of the intelligent system is achieved through keyword library expansion and neural network training sample overlay, iteratively improving the recognition accuracy of the intelligent system. Experimental validation demonstrates that the implemented intelligent system in this paper can increase the correct execution rate of user commands by 34%, significantly enhancing the command execution accuracy of the voice-controlled system.