RETRACTED ARTICLE: Voice-assisted translation of English vocabulary for offshore surface water temperature and trade

Abstract

Due to the gradual improvement of computing power and the development of big data, the error rate of voice recognition systems and voice assistance functions gradually decreases with the gradual application of deep learning. In terms of commercial contracts, it is a legally binding text. This article first analyzes the theory of functional equivalence translation and then analyzes the theory of functional equivalence translation from the perspective of professionalism and accuracy and determines the principles of business contract English vocabulary translation. At the same time, it studies English in terms of vocabulary equivalence. In the process of teaching trade English, some common vocabulary in trade English is easy to be misunderstood. This article analyzes these common translation errors and their main causes and proposes some appropriate solutions. Business English vocabulary translation must follow the principle of pragmatic equivalence, and the translation must be flexible to deal with communication obstacles caused by cultural background, language habits, and other factors, because they are subject to two different language and cultural characteristic rules (English and Chinese). The seasonal autoregressive summed moving average (ARIMA) model is used to simulate the time series of the surface water temperature in the coastal waters, and the structure of the model is determined through the principle of irrelevance and simplicity. On this basis, the optimal ARIMA prediction model is established and the surface water temperature of the coastal waters is monthly. The prediction results are consistent with the monthly change trend of the sea surface temperature, indicating that the model is suitable for predicting the offshore surface temperature.