Translation method, device and equipment based on machine learning and storage medium

Abstract

The invention discloses a translation method, device and equipment based on machine learning, and a storage medium, and relates to the field of artificial intelligence, and the method comprises the steps: obtaining a sentence of a first language type; dividing the sentence into at least two word segmentation sequences by adopting different word segmentation devices; generating a word graph structure of the sentence according to the at least two word segmentation sequences; calling an encoder to convert the word graph structure into an intermediate vector representation of the sentence; and calling a decoder to convert the intermediate vector representation into a sentence of a second language type. Because the word graph represents the possibility of covering various word segmentation of the sentence, the problem that wrong segmentation is generated in word segmentation can be solved, the problem that wrong semantics or ambiguity is generated in the sentence due to the fact that wrongsegmentation is generated in word segmentation, and irreparable damage is caused to the semantics of the sentence is solved, and the translation accuracy of a machine translation model is improved.

Description

technical field [0001] The embodiments of the present application relate to the field of artificial intelligence, and in particular to a translation method, device, device and storage medium based on machine learning. Background technique [0002] The translation system based on machine learning is currently the mainstream translation system. A typical neural network model used in a machine learning-based translation system includes: an encoder and a decoder. [0003] When using the neural network model for translation, the user inputs a sentence in the first language, and the sentence is expressed as a word sequence through word segmentation. The encoder converts the word sequence into an intermediate vector, and the decoder converts the intermediate vector into a sentence in the second language. [0004] However, because word segmentation may produce wrong divisions, resulting in wrong semantics or ambiguity in the sentence, which will cause irreparable damage to the sema...

AI Technical Summary

Problems solved by technology

[0005] The embodiment of the present application provides a translation method, device, device, and storage medium based on machine learning, which can solve the problem of wrong segmentation caused by word segmentation, resulting in wrong semantics or ambiguity in sentences, thereby causing irreparable damage to the semantics of sentences. less effective problem

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