Real-Time Optimization of Speech Processing Based on Deep Learning
Aiming at the real-time challenge of speech processing system based on deep learning, an optimization method of connection pruning is proposed to improve the real-time performance of speech recognition. Through in-depth study of the basic principle of speech recognition system based on deep learning, the method of connecting pruning is introduced to optimize the real-time performance of Recurrent Neural Network (RNN). The LibriSpeech data set is used to compare the optimization method with the traditional method, and the results show that the optimization method can effectively improve the recognition accuracy and operation efficiency of the model.
deep learningspeech recognitionRecurrent NeuralNetwork (RNN)connecting pruning
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