Design of an Embedded Speech Recognition System Based on Wavelet Neural Network
Aiming at the problem of resource limitation in embedded speech recognition,a lightweight recognition scheme based on wavelet neural network is proposed.This scheme uses wavelet transform to extract the time-frequency domain features of speech signals,and combines the nonlinear fitting ability of wavelet neural network to build an efficient speech recognition model.The empirical study shows that the scheme achieves 80.17%frame recognition accuracy on TIMIT data set,which not only meets the real-time constraints,but also significantly improves the performance of embedded speech recognition system,providing a new idea for the application deployment of intelligent voice interaction in resource-constrained scenarios.
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