Statistical machine translation method and system based on dependency tree

A technology dependent on edges and relationships, applied in the direction of instruments, calculations, special data processing applications, etc., can solve problems such as inability to reorder, accuracy and flexibility to be improved

Inactive Publication Date: 2014-12-24
INST OF COMPUTING TECH CHINESE ACAD OF SCI
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Problems solved by technology

This type of method directly maps the source language dependency tree to the target language string, and cannot reorder the fragments of the gene

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  • Statistical machine translation method and system based on dependency tree
  • Statistical machine translation method and system based on dependency tree
  • Statistical machine translation method and system based on dependency tree

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Embodiment Construction

[0043] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below through specific embodiments in conjunction with the accompanying drawings. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0044]In order to better understand the present invention, first briefly introduce the basic process of the dependency tree and the existing statistical machine translation method based on the dependency tree. Each node in the dependency tree of a sentence corresponds to a word in the sentence, and each directed edge in the dependency tree represents the relationship between a pair of words, and the direction is from the central node (also called the head node) to the Decorator nodes (also known as dependent nodes). Except for the root node, each node has one and only one directed edg...

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Abstract

The invention provides a statistical machine translation method based on a dependency tree. According to transformation rules extracted from a bilingual corpus, each dependency side of the dependency tree of source language sentences is transformed into corresponding target language phase dependency sides, and the obtained target language phase dependency sides are spliced to generate a target language translation. The method combines the advantages of a dependency syntax model and adopts a mode of analysis-transformation-generation to divide a translation process into three stages, the three processes can be respectively and independently modeled and the more accurate control of the generation process of target language sentences becomes possible. The transformation based on dependency sides reserves more knowledge, can tolerate a higher syntax non-isomorphism phenomenon and can obtain performance better than that of the current mainstream translation method based on phase models.

Description

technical field [0001] The invention belongs to the technical field of natural language processing, and in particular relates to a statistical machine translation method based on a dependency tree. Background technique [0002] Statistical machine translation is a hot topic in recent years. Along with its development process, it can be roughly divided into three categories: word-based translation, phrase-based translation and syntax-based translation. Although most of the current mainstream translation systems still use phrase-based translation models, syntax-based translation models have received more and more attention in recent years. Compared with the translation model based on words or phrases, the translation model based on syntax has both grammatical and semantic information, shows a better long-distance sequencing ability, and can better generalize the hierarchical structure of the language. modeling. But most syntax-based translation models (e.g., dependency pars...

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Application Information

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IPC IPC(8): G06F17/28
Inventor 陈宏申谢军孟凡东姜文斌刘群
Owner INST OF COMPUTING TECH CHINESE ACAD OF SCI
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