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Sentence-level bilingual alignment method and system

A sentence-level, bilingual technology, applied in the field of sentence-level bilingual alignment methods and systems, can solve problems such as labor and time-consuming, unfavorable sentence alignment efficiency, etc., to improve efficiency, realize automatic sentence alignment, and reduce manual participation.

Active Publication Date: 2020-01-21
龙马智芯(珠海横琴)科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] Parallel corpora are important data for translation algorithms based on natural language processing. Parallel / corresponding corpora are bilingual / multilingual corpora composed of source texts and parallel corresponding target language texts. The degree of alignment can be divided into word-level , sentence-level, paragraph-level, and article-level. Among them, the sentence-level parallel corpus is the most commonly used corpus. Therefore, the paragraph-level and article-level parallel corpora are often converted into sentence-level parallel corpora. However, in the corpus , there is not necessarily a one-to-one correspondence between the original text and the translation, so it is usually necessary to manually split the corpus of paragraphs and chapters into one-to-one sentences. This method requires a lot of manpower and time, which is not conducive to sentence Improvement in Alignment Efficiency

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  • Sentence-level bilingual alignment method and system
  • Sentence-level bilingual alignment method and system
  • Sentence-level bilingual alignment method and system

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Embodiment Construction

[0050] The present invention is described below based on examples, but the present invention is not limited to these examples. In the following detailed description of the present invention, some specific details are described in detail, and in order to avoid obscuring the essence of the present invention, known methods, procedures, procedures, and components are not described in detail.

[0051] Additionally, those of ordinary skill in the art will appreciate that the drawings provided herein are for illustrative purposes and are not necessarily drawn to scale.

[0052]Unless the context clearly requires, throughout the specification and claims, "comprises", "comprises" and similar words should be interpreted in an inclusive sense rather than an exclusive or exhaustive meaning; that is, "including but not limited to" meaning.

[0053] In the description of the present invention, it should be understood that the terms "first", "second" and so on are used for descriptive purpo...

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Abstract

The invention discloses a sentence-level bilingual alignment method and system, and the method comprises the steps: S1, carrying out the processing of two to-be-aligned texts, and obtaining a first statement list and a second statement list; S2, calculating the text similarity between each statement in the first statement list and each statement in the second statement list; Step S3: correcting the text similarity according to the position of the corresponding statement of the statement in the first statement list in the text and the position of the corresponding statement of the statement inthe second statement list in the other text. obtaining a statement matching degree between each statement in the first statement list and each statement in the second statement list; and S4, obtaininga statement alignment result of the two texts according to the statement matching degree of each statement in the first statement list and each statement in the second statement list. The statement alignment efficiency can be improved.

Description

technical field [0001] The invention relates to the technical field of natural language processing, in particular to a sentence-level bilingual alignment method and system. Background technique [0002] Parallel corpora are important data for translation algorithms based on natural language processing. Parallel / corresponding corpora are bilingual / multilingual corpora composed of source texts and parallel corresponding target language texts. The degree of alignment can be divided into word-level , sentence-level, paragraph-level, and article-level. Among them, the sentence-level parallel corpus is the most commonly used corpus. Therefore, the paragraph-level and article-level parallel corpora are often converted into sentence-level parallel corpora. However, in the corpus , there is not necessarily a one-to-one correspondence between the original text and the translation, so it is usually necessary to manually split the corpus of paragraphs and chapters into one-to-one senten...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F40/205G06F40/211G06F40/58
CPCG06F40/205G06F40/211G06F40/58
Inventor 聂镭李睿聂颖郑权张峰
Owner 龙马智芯(珠海横琴)科技有限公司