Machine Automatic Translation System Based on Artificial Intelligence Processor Design

In response to the problem of low accuracy in the translation process of traditional machine translation machines, the author proposes to use an artificial intelligence-based automatic machine translation model to improve the speed and accuracy of machine translation. We complete system hardware design from user design and hardware design; Using the three-layer architecture to create an English-Chinese translation network architecture, we create a sequential model to extract the main content of the English-Chinese translation, collect a dataset of these features, determine their behavior, and complete the part of the automatic special extraction algorithm, English and Chinese machine translation. According to the test results, the traditional method 1 system and traditional method 2 have the highest accuracy of 94.4 and 94.7 in the number of iterations and equipment overuse. In practice, the number of iterations can be increased to 200, and the accuracy of 98.4 can be achieved, which can meet the actual needs. Machine translation based on artificial intelligence technology has improved the speed and accuracy of sentence translation compared to text-based machine translation.