Domain parallel corpus generation method and translation model training method

Abstract

The invention discloses a field parallel corpus generation method and a translation model training method, and belongs to the field of machine translation in natural language process.The method comprises the steps that a machine translation model is used for aligning chapter-level corpus and sentence-level corpus in a parallel corpus material library, chapter-level parallel corpus and sentence-level parallel corpus are generated after alignment, and the chapter-level parallel corpus and the sentence-level parallel corpus are used for training the chapter-level parallel corpus and the sentence-level parallel corpus; and forming a field parallel corpus. The field parallel corpora can be generated, self-updating of the supervised machine translation model is achieved, universality is achieved, meanwhile, the content quality of the field parallel corpora is improved, correctness of field term translation in the translation process is guaranteed, cost is reduced, and the method is suitable for popularization and application. Self-circulation of field parallel corpus generation and machine translation in supervised machine translation is achieved, and meanwhile efficiency is improved.

Description

technical field [0001] The invention relates to the field of machine translation in natural language processing, and more particularly, to a method for generating parallel corpora in the field and a method for training translation models. Background technique [0002] Machine translation belongs to the category of computational linguistics, which studies the technology of translating text from one natural language into another natural language by means of computer programs, namely machine translation models. There are two types of machine translation models: supervised and unsupervised. With the parallel corpus generation technology, the supervised translation model can realize more complex automatic text translation, and can handle different grammatical structures, vocabulary recognition and idiom correspondence. [0003] Parallel corpus refers to the text placed in parallel with the translation. Parallel text alignment technology refers to the technology of determining t...

AI Technical Summary

Problems solved by technology

[0006] Previous studies on the generation of parallel corpora mainly focused on the scale and quality of parallel corpora, and rarely involved research on the generation of parallel corpora in the field

At the same time, due to the relatively difficult collection and processing of domain corpus, the generation of parallel corpus for a specific domain often relies on manual translation, which makes the current domain corpus extremely scarce, and even some domains do not meet the requirements of machine translation model training at all. Corpus of

[0007] At present, the existing technology has the following technical problems: 1) The domain parallel corpus is scarce, which cannot meet the needs of the machine translation model; 2) The existing domain parallel corpus has poor versatility; 3) In the process of generating the existing parallel corpus, there is no guarantee The problem of correct translation of domain terms; 4) The cost and efficiency of manually determining the generation of parallel corpus in the domain are high and low

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