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Method and device for long statement segmentation aiming at neural machine translation

A technology of machine translation and segmentation device, applied in the field of language translation, can solve the problems of decreased translation effect and poor translation effect, etc.

Active Publication Date: 2016-08-31
IOL WUHAN INFORMATION TECH CO LTD
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Problems solved by technology

[0004] Although the NMT model based on the encoder-decoder structure can achieve good translation results, when the source sentence is too long, its translation effect will decrease
In particular, as the length of the source sentence increases, its translation effect will become worse and worse to a certain extent

Method used

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  • Method and device for long statement segmentation aiming at neural machine translation
  • Method and device for long statement segmentation aiming at neural machine translation
  • Method and device for long statement segmentation aiming at neural machine translation

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Embodiment Construction

[0090] The following will clearly and completely describe the technical solutions in the embodiments of the application with reference to the drawings in the embodiments of the application. Apparently, the described embodiments are only some of the embodiments of the application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0091] see figure 1 , which shows the flow of Embodiment 1 of the neural machine translation-oriented long sentence segmentation method provided by the present application. Such as figure 1 As shown, this embodiment may specifically include step S101 to step S104.

[0092] Step S101: After obtaining the source sentence to be translated, determine the length of the source sentence.

[0093] The sentence to be translated may be called a source sentence, and the translated sentence ...

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Abstract

The application provides a method for long statement segmentation aiming at neural machine translation. The method comprises the steps that before statement translation based on an NMT model, direct input of source statements into the NMT is replaced by segmentation of statements into short sub-statements, and each sub-statement is successively input the NMT model, so that each segmented sub-statement is translated successively by the NMT model respectively; and then the translated sub-statements are directly spliced into a complete sub-statement. The sub-statements which are input into the NMT model for translation are short and translation accuracy of the NMT model is high, so that the accuracy for statement translation is increased. In addition, the application also provides a device for the long statement segmentation aiming at the neural machine translation so as to ensure application and implementation of the method in practice.

Description

technical field [0001] This application relates to the technical field of language translation, and more specifically, to the long sentence segmentation technology for neural machine translation. Background technique [0002] At present, Neural Machine Translation (Neural Machine Translation, abbreviated as NMT) based on deep learning has attracted more and more attention. In the NMT field, a common NMT model is a model based on the encoder-decoder structure. The NMT model mainly translates a sentence in a certain language (hereinafter referred to as a source sentence) into a sentence in another language (hereinafter referred to as a target sentence). [0003] Taking Chinese-English translation as an example, the model based on the encoder-decoder structure mainly obtains the encoding vector after the source sentence is encoded by the encoder, and then uses the decoder to decode the encoding vector to translate into the corresponding English sentence. In fact, the translat...

Claims

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Application Information

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IPC IPC(8): G06F17/28G06F17/24G06F17/27
CPCG06F40/166G06F40/211G06F40/58
Inventor 熊德意邝少辉
Owner IOL WUHAN INFORMATION TECH CO LTD
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