The use of machine translation algorithm based on residual and LSTM neural network in translation teaching.

ABSTRACT: With the rapid development of big data and deep learning, breakthroughs have been made in phonetic and textual research, the two fundamental attributes of language. Language is an essential medium of information exchange in teaching activity. The aim is to promote the transformation of the training mode and content of translation major and the application of the translation service industry in various fields. Based on previous research, the SCN-LSTM (Skip Convolutional Network and Long Short Term Memory) translation model of deep learning neural network is constructed by learning and training the real dataset and the public PTB (Penn Treebank Dataset). The feasibility of the model's performance, translation quality, and adaptability in practical teaching is analyzed to provide a theoretica

SUBMITTER: Ren B 

PROVIDER: S-EPMC7676682 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature