Translation machine testing method based on syntax tree pruning

A translation machine and syntax tree technology, applied in the field of machine translation, can solve problems such as difficulty in testing translation machines

Pending Publication Date: 2022-03-25
NANJING UNIV
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AI Technical Summary

Problems solved by technology

[0006] The present invention solves the existing problem of difficult translation machine testing by proposing a translation machine testing method based on grammar tree pruning, and then

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  • Translation machine testing method based on syntax tree pruning
  • Translation machine testing method based on syntax tree pruning
  • Translation machine testing method based on syntax tree pruning

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Embodiment Construction

[0031] In order to better understand the technical content of the present invention, specific examples are given and described as follows in conjunction with the accompanying drawings.

[0032] figure 1 It is a flow chart of the translation machine testing method based on syntax tree pruning implemented by the present invention.

[0033] Construct a syntax tree: use the relevant syntax analysis library to obtain the dependent syntax structure information, extract the semantic backbone and related semantic components, and construct a tree storage structure from triples.

[0034] Sentence type detection: According to the dependent syntax tree of the sentence extracted from the source sentence, the sentence type detection is performed on the dependent syntax tree. Among them, the sentence type refers to the basic types of sentences in linguistics, and other types are extended from these basic types. There are five basic types of sentences, including SV, SVC, SVO, SVOO, and SVOC....

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Abstract

The invention relates to a machine translation test method. According to the method, a dependency syntax tree is constructed for sentences, pruning is performed on the syntax tree according to a specific rule, validity of the sentences is destroyed based on a group of deletion operators of a dependency syntax tree level, and words or phrases are deleted from the original sentences to generate new sentences with effective grammar and semantics. And inputting the original text and the newly generated sentences into a tested machine translation system, calculating bag-of-word distances, sequencing and amplifying the sentences according to the bag-of-word distances, selecting five sentences with the largest distance, manually labeling the original sentence and the translated sentence results, marking wrong sentences, and completing the test of the machine translation system. The invention aims to solve the problem that the test performance is mainly limited by the maturity of an adopted language model due to the fact that a test case is mainly generated by replacing a part of words in a sentence in the current machine translation test. When the data is amplified, the invariance of the basic structure of the sentence is ensured, so that more pairs of errors are found, and most of the errors cannot be found by a previous machine translation test technology.

Description

technical field [0001] The invention belongs to the field of machine translation in information technology, and is particularly suitable for machine translation testing in machine translation. The purpose of the invention is to generate test sentences in machine translation testing, and it is a translation machine testing method capable of generating a large number of test sentences. Background technique [0002] Machine translation is the task of using computers to convert one natural language into another natural language, and it is one of the hot issues in the field of artificial intelligence research. In recent years, with the development of deep learning, neural machine translation models based on sequence-to-sequence structures have achieved better results than statistical machine translation models in translation tasks of multiple language pairs, and have been widely used in commercial translation systems. Although the actual application effect of the commercial trans...

Claims

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Application Information

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IPC IPC(8): G06F40/211G06F40/30G06F40/253G06F40/58
CPCG06F40/211G06F40/30G06F40/253G06F40/58
Inventor 房春荣王擎宇张犬俊刘佳玮陈振宇
Owner NANJING UNIV
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