Common speech recognition intelligent toy car performs well in high signal-to-noise ratio(SNR)environment,but their speech recognition performance is poor in low SNR environment,which leads to the fact that the car is unable to perform relevant actions effectively.To this end,this paper proposes a speech recognition intelligent toy car design suitable for low SNR environment.The car collects speech signal through microphone,uses deep learning algorithm and speech recognition module for speech recognition,and the main control chip controls the motor operation according to the speech recognition result to control the toy car to perform forward,backward,left or right turn actions.The car performs obstacle avoidance through in-frared photoelectric sensor in the process of traveling.Under the low SNR environment,the designed toy car has a high speech recognition accuracy rate and can correctly realize the established actions,which has a better application prospect.
关键词
低信噪比/深度学习/语音识别/玩具小车
Key words
low signal-to-noise ratio/deep learning/speech recognition/toy car
维普
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