The application provides a keyword detection method and related equipment. The method comprises: performing
feature extraction on a to-be-processed voice
signal to obtain acoustic features; and inputting the acoustic features into a trained neural
network model to output a keyword detection result, wherein the trained neural
network model is a dynamic
binary neural network. According to the technical solution, the to-be-processed voice
signal is first subjected to
feature extraction to obtain acoustic features, and then the acoustic features are input into the trained dynamic
binary neural network model to output a keyword detection result. In this way, the parameter quantity and the calculation quantity in the neural
network model are greatly reduced, the data storage space is reduced, the wake-up speed is improved, and the
power consumption of the detection
system is effectively reduced, thereby reducing the difficulty of hardware implementation. Meanwhile, the recognition accuracy of the keyword detection result is effectively improved.