Japanese verb recognition and part-of-speech tagging method for neural network machine translation

A machine translation and neural network technology, applied in the field of machine translation, can solve problems that cannot fully satisfy the deep learning of neural networks, and achieve the effects of ensuring recognition accuracy, improving translation quality, and improving accuracy

Active Publication Date: 2021-10-08
北京中献电子技术开发有限公司
View PDF8 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, from the design point of view, this method is more suitable for statistical algorithms. It cannot fully meet the needs of neural networks in terms of the fineness of lexical analysis and the data dimensionality reduction required for deep learning of neural networks. The need for network deep learning

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Japanese verb recognition and part-of-speech tagging method for neural network machine translation
  • Japanese verb recognition and part-of-speech tagging method for neural network machine translation
  • Japanese verb recognition and part-of-speech tagging method for neural network machine translation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0048] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure, and to fully convey the scope of the present disclosure to those skilled in the art.

[0049] Those skilled in the art can understand that, unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art to which this invention belongs. It should also be understood that terms, such as those defined in commonly used dictionaries, should be understood to have meanings consistent with the meanings in the c...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to the technical field of machine translation, in particular to a method and system for recognizing Japanese verbs and part-of-speech tagging for neural network machine translation. The method comprises the following steps: S100, delete the special vocabulary of the left adjacency sign and the end sign in the Japanese text; S200, search and select to obtain the candidate verb; S300, obtain the candidate verb to be restored by segmentation, restore the candidate verb, if verify its If it is correct, the candidate verb is successfully restored; S400. Segment the successfully restored verb and its inflected ending, and mark the part of speech and its grammatical meaning. The present invention improves the accuracy of verb recognition by adding a secondary judgment mechanism and perfecting the recognition and processing rules of compound verbs; at the same time, verbs and their modified endings are segmented into stems, endings, possible expressions, tense, state, and modality. Effectively improve the accuracy of lexical analysis, thereby effectively improving the quality of translation.

Description

technical field [0001] The invention relates to the technical field of machine translation, in particular to a method and system for recognizing Japanese verbs and part-of-speech tagging for neural network machine translation. Background technique [0002] Machine translation, also known as automatic translation, is the process of using a computer to convert one natural language (source language) into another natural language (target language). With the increasing international economic cooperation, the translation quality and efficiency of the translation industry have encountered great challenges, and with the rapid development of artificial intelligence, the huge potential of machine translation in the translation industry has gradually emerged. Manual translation is stressful, costly, and time-consuming. From the perspective of social development trends, it is necessary to develop and promote machine translation engines that can initially replace manual labor and reduce ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G06F40/253G06F40/30G06F40/58G06N3/04G06N3/08
CPCG06N3/08G06N3/045
Inventor 张孝飞诸敏刚葛昱晖陈莉莉周聪
Owner 北京中献电子技术开发有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap