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A Chinese grammatical error detection method based on textualized word vectors

A technology for grammatical errors and detection methods, applied in the field of information processing, can solve problems such as poor use of Chinese vocabulary and different meanings

Active Publication Date: 2019-05-28
BEIJING UNIV OF POSTS & TELECOMM
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  • Description
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AI Technical Summary

Problems solved by technology

However, most of the work did not make good use of the information expressed in Chinese vocabulary, ignoring the fact that the same word may have different meanings in different texts

Method used

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  • A Chinese grammatical error detection method based on textualized word vectors
  • A Chinese grammatical error detection method based on textualized word vectors
  • A Chinese grammatical error detection method based on textualized word vectors

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Embodiment Construction

[0013] Next, embodiments of the present invention will be described in more detail.

[0014] Figure 1 It is a network structure diagram of the error detection method provided by the present invention, which includes:

[0015] Step S1: the text word vectorization of input;

[0016] Step S2: the cyclic neural network forms a mask about the importance of each component in the word vector;

[0017] Step S3: Text matrix reconstruction;

[0018] Step S4: the cyclic neural network extracts context information;

[0019] Step S5: the forward neural network calculates the error score of each word;

[0020] Step S6: use the error score to infer the error location;

[0021] Each step will be described in detail below:

[0022] Step S1: Text word vectorization. The present invention first establishes a mapping dictionary from words to word vector numbers, and maps each word in the text to a corresponding word number. Create a word vector matrix, each row number corresponds to the ...

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Abstract

The invention discloses a Chinese grammatical error detection method and device, belonging to the field of information processing. The characteristics of this method include: first vectorize the input text words and connect them to form a text matrix; then use the cyclic neural network to form a mask about the importance of each component in the word vector; reconstruct the text matrix; use the cyclic neural network to extract context information; Error scores are calculated for each word using a feed-forward neural network; error locations are inferred using the error scores. The present invention improves the detection effect of Chinese grammar by combining text-based word vectors, and has great use value.

Description

technical field [0001] The invention relates to the field of information processing, in particular to a neural network-based Chinese grammatical error detection method. Background technique [0002] Chinese grammatical error detection is a relatively new task in Chinese natural language processing. The purpose is to judge whether the sentences written by non-Chinese native speakers are wrong, and give error messages. [0003] At present, the most common Chinese grammar error detection method is to complete the error detection task as a supervised sequence labeling task. The more common grammatical error detection includes N-Gram, recurrent neural network, etc. However, these networks are very dependent on artificially designed features and require more artificial features to be added. Recently, since the neural network can learn the features of the text by itself to replace the complex artificial features, many works are trying to apply the neural network to Chinese gramma...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/27G06N3/04G06N3/08
CPCG06N3/084G06F40/211G06N3/044G06N3/045
Inventor 李思赵建博李明正徐雅静
Owner BEIJING UNIV OF POSTS & TELECOMM
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