With the rapid progress of computer technology, software technology based on deep learning presents a diversified development trend. Machine learning technology is based on deep learning technology. It can optimize the performance of computer programs to ensure the enhancement of machine translation ability [1]. The progress of machine learning technology makes computer-aided translation software come into being. The purpose of this paper is to design a computer-aided translation software system using deep learning technology. The writing method of this paper includes theoretical analysis and practical basis, and the basic conclusion of practice is obtained through theoretical analysis. The results show that deep learning can indeed help improve the efficiency and update speed of auxiliary translation software. On this basis, this paper mainly introduces the functional design and main implementation methods of computer-aided translation software.
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