Machine translation method and machine translation systems for automatically recognizing chapter based on fields

Abstract

The invention belongs to the technical field of processing or conversion of natural languages, and discloses a machine translation method and machine translation systems for automatically recognizinga chapter based on fields. The machine translation method comprises the steps of dividing sentences to be translated to the corresponding fields; calling the translation systems corresponding to the fields for each sentence to be translated in the chapter according to corresponding field information to translate the sentences; merging the translated sentences to obtain a final chapter translationresult. On the basis of a traditional machine translation mechanism, improvement is conducted, a classifying algorithm is adopted to divide the fields of the sentences to be translated, and then the sentences are put into the translation systems corresponding to the fields for translation. Compared with a traditional method of manually selecting the translation systems of the fields for translation, the time for manually judging the fields to which the sentences belong can be saved. Compared with the mode of directly utilizing a universal translation system for translation, the translation accuracy can be effectively improved.

Description

Technical field [0001] The invention belongs to the technical field of natural language processing or conversion, and in particular relates to a field-based automatic text recognition machine translation method and a machine translation system. Background technique [0002] At present, the existing technology commonly used in the industry is as follows: Machine translation is a process of using machine learning algorithms to learn the correlation between two languages ​​from bilingual parallel data, and then using learning rules to transform one natural language into another. The development of machine translation technology has been closely following the development of disciplines such as computer technology, information theory, and linguistics. Machine translation has experienced a period of creation, frustration, recovery, and a new period since the 1930s and 1940s. The new era began in 1990 and has experienced rule-based machine translation, statistics-based machine translat...

AI Technical Summary

Problems solved by technology

[0004] (1) No matter which field the sentence to be translated entered by the user belongs to, it is taken as input and translated by a general system. The correlation between the sentence to be translated and the training set of the corresponding system is not closely related

[0005] (2) The user selects a specific domain translation system, inputs the sentence to be translated, and the corresponding domain translation system gives the corresponding translation. The input is text, and the sentences in the text may belong to different domains, so it is necessary to manually identify the sentence to which each sentence belongs. Domain, input corresponding domain translation system, the method is not efficient enough

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