Translation model training method, translation method and translation model training device

A translation model and training method technology, applied in natural language translation, etc., can solve problems such as unstable model training and complicated methods for translation model robustness, and achieve stable model training, improved robustness, and guaranteed quality

Pending Publication Date: 2022-03-18
UNIV OF SCI & TECH OF CHINA +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This patented technology allows for better understanding about how translated languages are used more efficiently than traditional techniques like concatenating them together with learning their characteristics. It uses both continuous variables (such as tokens) and discrete variables called signatures that represent these characters' unique attributes such as contextual relevancy between words). By doing this we aimed at improving speech recognition systems while reducing background noise levels without adding any extra components.

Problems solved by technology

This patented technical problem addressed in this patents relates to improving the accuracy or reliability of translating from one type of document into another without generating too much noise during word recognition processing due to imperfections such as line alignments between words being used for interpretation.

Method used

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  • Translation model training method, translation method and translation model training device
  • Translation model training method, translation method and translation model training device
  • Translation model training method, translation method and translation model training device

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Embodiment Construction

[0079] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments It is a part of embodiments of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0080] In order to ensure the translation quality, the scanning translation pen needs to follow certain specifications when using it. For example, when capturing images of paper documents, it is recommended that the scanning translation pen and the desktop form an angle of 45 degrees. Line alignment of text to be translated in paper documents, etc.

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Abstract

The embodiment of the invention provides a translation model training method and device and a translation method and device. The model training method comprises the following steps: respectively inputting a source language statement and a noisy source language statement in a parallel bilingual sentence pair into a translation model to obtain a first prediction target language statement and a second prediction target language statement, first prediction probability distribution and second prediction probability distribution of the translation model and/or first feature vectors and second feature vectors output by the hidden layers are obtained respectively; based on the first prediction target language statement and the target language statement in the parallel bilingual sentence pair, the second prediction target language statement and the target language statement corresponding to the noise-added source language statement, the first feature vector and the second feature vector and/or the first prediction probability distribution and the second prediction probability distribution; determining the current training loss of the translation model, and adjusting the parameters of the translation model. According to the embodiment of the invention, the robustness of the translation model can be improved, the training method is simple, and model training is stable.

Description

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Claims

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Application Information

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Owner UNIV OF SCI & TECH OF CHINA
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