big sentence database translation method

Abstract

The invention discloses a large sentence library based translation method. The technical problem to be solved is to improve the accuracy of machine-based language translation. The method of the invention comprises the steps of setting a source language large-sentence-library module, a target language large-sentence-library module, a polysemous sentence library module, and a synonymous sentence library module; inputting a sentence to be translated; finding from the source language large-sentence-library module, source statement sentences the same as the input sentence; finding from the polysemous sentence library module and the synonymous sentence library module, polysemous sentences and synonymous sentences; selecting the sentences having the closest meaning; finding from the target language large-sentence-library module, corresponding sentences in target language. Compared with the prior art, the method replaces a word bank with a sentence library; the translation means of complete sentences corresponding to complete sentences is adopted, so that various grammar mistakes due to the process where a source language sentence is divided into single words that are translated to compose a sentence are avoided; handling by the polysemous sentences and synonymous sentences is adopted, so that translation accuracy is improved significantly.

Description

technical field

[0001] The invention relates to a language translation method, in particular to a machine language translation method. Background technique

[0002] Language machine translation first appeared in the 1940s and has been continuously improved with the development of computer technology. In the past ten years, the traditional machine translation systems and methods developed along the way have been continuously improved. The mainstream state-of-the-art machine translation is to first establish the thesaurus or fonts of the source language and the target language respectively. When translating a sentence, the machine splits the input sentence in the source language into components such as subject, predicate, object, and adverbial, and then finds out the corresponding words in the target language according to the correspondence between words in the two thesaurus Words in the target language are combined into sentences to obtain translated sentences. In differen...

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