Candidate phrase querying method and aided translation system for computer aided translation

Abstract

The invention provides a method and a system of computer aided translation, which utilize the aided translation information as intermediate information, the user memory bank and the dictionary in computer translation so as to correct and improve the computer automatic translation result based on the computer translation result, wherein by adopting the candidate phrase querying method based on the AC automation, the candidate phrase query problem is solved within linear complicity, and the efficiency of aided translation is greatly improved; the sorting problem of the phrases of different sets is solved by adopting the candidate phrase sorting method based on Kalman filter, and the weight of the candidate phrase sets is continuously optimized by analyzing the translation history of the user, so as to improve the precision in recommending the candidate phrases.

Description

technical field [0001] The invention belongs to the field of computer-aided translation, in particular to a method for recommending candidate phrases in the computer-aided translation process. Background technique [0002] With the rapid development of science and technology and the Internet, computer and network technology has penetrated into every aspect of our work and life. In the field of translation, nothing is more exciting than computer-aided translation technology CAT (Computer Aided Translation). There are two different ways of thinking in the design of computer-aided translation system: one is machine translation (Machine Translation), and the other is translation memory (Translation Memory). [0003] In recent years, machine translation technology has made great progress, but due to the complexity of natural language, the translation of machine translation is difficult to achieve a perfect level. At the same time, the result of traditional machine translation o...

AI Technical Summary

Problems solved by technology

The time complexity of this algorithm is high. As the length of the source language sentence increases and the number of candidate phrases increases, the query time will increase rapidly.

According to the inventor's experimental statistics, when the length of the source language sentence is 400 characters, the query time reaches about 4 seconds. This speed is obviously unbearable for the machine translation system, and the user experience is poor.

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