Collaborative English Translation (CET) Tools Based on Cloud Translation Platform

How to coordinate the task allocation and process arrangement between the translator and the computer to reduce the labor intensity of the translator and improve the efficiency of translation is still a difficult problem and requires more in-depth research. Based on the CET tool of the cloud translation platform, this paper studies and discusses the function and translation process of CET; proposes a collaborative translation quality scoring algorithm, and uses the collaborative translation quality scoring algorithm to test the accuracy of cet and the English translation of different classifiers in the economic field, as well as the experimental results of the combination of oversampling and undersampling in the network neighborhood. The results show that the recall rate and accuracy rate of collaborative translation ensemble learning are higher than ordinary translation in the network and economic fields. The recall rate data is as high as 97%, with an accuracy rate of 79%.