Machine translation model training method, language translation method and equipment

A machine translation and model technology, applied in natural language translation, etc., can solve problems affecting the performance of neural machine translation models, achieve high translation quality and fidelity, and improve performance

Pending Publication Date: 2021-11-26
TENCENT TECH (SHENZHEN) CO LTD +1
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Problems solved by technology

Therefore, the existence of language coverage bias in bilingual parallel data will affect the performance of neural machine translation models trained by bilingual parallel data

Method used

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  • Machine translation model training method, language translation method and equipment
  • Machine translation model training method, language translation method and equipment
  • Machine translation model training method, language translation method and equipment

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Embodiment Construction

[0065] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. 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.

[0066] First, for ease of understanding, before introducing the training method of the machine translation model provided by the embodiment of the present application, the following introduces the relevant terms involved in the invention examples of the present application.

[0067] DL: Deep Learning, deep learning, is a branch of machine learning. It is an algorithm that attempts to perform high-level abstraction on data using multiple processing ...

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Abstract

The embodiment of the invention discloses a training method of a machine translation model, a language translation method and equipment, and relates to the field of machine translation of natural language processing. The method comprises the steps of dividing data in a first bilingual parallel database into source language data and target language data, performing fine adjustment on an initial machine translation model through the source language data to obtain a fine-adjusted machine translation model, and performing a translation task by applying the fine-adjusted machine translation model. The influence of language coverage deviation existing between data of different languages on the machine translation model can be eliminated, so that the performance of the machine translation model obtained by training through the method is improved, and translations with relatively high quality and loyalty can be obtained by applying the model.

Description

technical field [0001] The invention relates to the field of natural language processing of artificial intelligence, in particular to a training method of a machine translation model, a language translation method and equipment. Background technique [0002] Neural machine translation has risen rapidly in recent years. Compared with statistical machine translation, neural machine translation is relatively simple in terms of model. It mainly includes two parts, one is an encoder and the other is a decoder. The encoder is to express the source language into a high-dimensional vector after a series of neural network transformations. The decoder is responsible for re-decoding (translating) this high-dimensional vector into the target language. [0003] The training of neural machine translation models is inseparable from large-scale, high-quality bilingual parallel data. Bilingual parallel data is usually translated by human translators, and the construction of large-scale bi...

Claims

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Application Information

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IPC IPC(8): G06F40/44G06F40/58
CPCG06F40/44G06F40/58
Inventor 涂兆鹏刘洋史树明王硕
Owner TENCENT TECH (SHENZHEN) CO LTD
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