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Machine translation method and device, electronic equipment and medium

A technology of machine translation and translation results, applied in the field of machine translation, can solve the problems of low accuracy and low efficiency of automatic translation, achieve clear boundaries of translation content and improve translation effect

Active Publication Date: 2019-04-30
BEIJING BAIDU NETCOM SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Embodiments of the present invention provide a machine translation method, device, electronic equipment, and medium to solve the problems of low accuracy and low efficiency of automatic translation in the prior art

Method used

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  • Machine translation method and device, electronic equipment and medium
  • Machine translation method and device, electronic equipment and medium
  • Machine translation method and device, electronic equipment and medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0025] figure 1 It is a flow chart of a machine translation method provided by Embodiment 1 of the present invention. This embodiment is applicable to automatic translation (machine translation), and the method can be executed by a machine translation device, which can use software and / or hardware implementation, and can be configured in electronic equipment, the electronic equipment includes terminals or servers, such as figure 1 As shown, the method includes:

[0026] S110. Obtain the source language sentence to be translated.

[0027] The source language sentence to be translated may be, for example, a word, phrase or sentence input by the user to be translated. When the system acquires the source language sentence to be translated, it can perform corresponding translation, for example, the acquired Chinese source language sentence.

[0028] S120. Using the pre-trained machine translation model, simultaneously provide the target language translation result of the source...

Embodiment 2

[0035] image 3 It is a flowchart of a machine translation model training method provided in Embodiment 2 of the present invention. On the basis of the above embodiments, optionally, the machine translation model is a neural network-based machine translation model, such as image 3 Shown, the training method of described machine translation model comprises:

[0036] S310. Obtain sample data, wherein the sample data includes a set of sample sentences in the source language, and each sample sentence is correspondingly marked with the coarse classification and fine classification to which it belongs, and the corresponding The target language translation results of .

[0037] Each sample sentence may include the source language sentence itself, its marked coarse classification and fine classification, and the translation result of the target language under the category formed by the coarse classification and fine classification. Exemplarily, a sample sentence may include: the sour...

Embodiment 3

[0063] Figure 5 is a schematic structural diagram of a machine translation device provided in Embodiment 3 of the present invention, as shown in Figure 5 As shown, the device can be implemented in the form of hardware and / or software, and can be configured in electronic equipment, and the device includes:

[0064] Source language sentence obtaining module 510, for obtaining the source language sentence to be translated;

[0065] The source language sentence translation module 520 is used to use the pre-trained machine translation model to simultaneously provide the target language translation result of the source language sentence and the category to which the source language sentence belongs, wherein the category includes rough classification and The fine classification under the coarse classification, the machine translation model is used in combination with the classification task of the source language sentence to give the target language translation result.

[0066] Opt...

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Abstract

The embodiment of the invention discloses a machine translation method and device, electronic equipment and a medium. The method comprises the steps that a to-be-translated source language sentence isacquired; wherein a pre-trained machine translation model is used for giving a target language translation result of the source language sentence and a category to which the source language sentencebelongs at the same time, the category comprises coarse classification and fine classification under the coarse classification, and the machine translation model is used for giving the target languagetranslation result in combination with a classification task of the source language sentence. According to the embodiment of the invention, the trouble of manually selecting the field by a user is avoided; meanwhile, a classification task and a translation task are executed; coarse classification and fine classification to which the coarse classification belongs are given in the classification task. Compared with the prior art, the method has the advantages that each field is classified in the same dimension instead of in the same dimension, so that the model is more targeted in a category classification stage, categories and fields described by source language sentences can be automatically identified, meanwhile, translation content boundaries responsible for each field are clearer, andthe translation effect is improved.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of machine translation, and in particular, to a machine translation method, device, electronic equipment, and medium. Background technique [0002] With the improvement of computer computing power and the explosive growth of multilingual information, machine translation plays an important role in today's translation field. It has the advantages of high speed and low cost, and can provide real-time and convenient translation services for ordinary users. [0003] In machine translation, for texts in professional fields, training translation models in different fields can greatly improve the translation effect in the corresponding fields. At present, some Internet translation systems have improved the translation effect by introducing domain information and optimizing data and models for each domain. However, the classification of these fields is relatively random and unsystematic. Dividi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/28G06F16/35
CPCG06F40/58Y02D10/00
Inventor 张睿卿何中军吴华王海峰
Owner BEIJING BAIDU NETCOM SCI & TECH CO LTD
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