Research on the Efficiency of Intelligent Algorithm for English Speech Recognition and Sentence Translatione
DOI:
https://doi.org/10.31449/inf.v45i2.3564Abstract
Machine translation has been gradually widely used to improve the efficiency of English translation. This paper briefly introduced the English speech recognition algorithm based on the back-propagation (BP) neural network algorithm and the machine translation algorithm based on the long short-term memory-recurrent neural network (LSTM-RNN) algorithm. Then, the machine translation algorithm was simulated and compared with BP-RNN and RNN-RNN algorithms. The results showed that the BP neural network algorithm had a lower word error rate and shorter recognition time than manual recognition; the LSTM-RNN-based machine translation algorithm had the lowest error rate of the translated words in the speech recognition results, and the translation gained the highest evaluation score from ten professional translators.
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