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Title:
DEEP CONTEXT-BASED GRAMMATICAL ERROR CORRECTION USING ARTIFICIAL NEURAL NETWORKS
Document Type and Number:
WIPO Patent Application WO/2019/024050
Kind Code:
A1
Abstract:
Disclosed herein are methods and systems for grammatical error detection. In one example, a sentence is received. One or more target words in the sentence are identified based, at least in part, on one or more grammatical error types. Each of the one or more target words corresponds to at least one of the one or more grammatical error types. For at least one of the one or more target words, a classification of the target word with respect to the corresponding grammatical error type is estimated using an artificial neural network model trained for the grammatical error type. A grammatical error in the sentence is detected based, at least in part, on the target word and the estimated classification of the target word.

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Inventors:
LIN HUI (CN)
WANG CHUAN (CN)
LI RUOBING (CN)
Application Number:
PCT/CN2017/095841
Publication Date:
February 07, 2019
Filing Date:
August 03, 2017
Export Citation:
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Assignee:
LINGOCHAMP INFORMATION TECH SHANGHAI CO LTD (CN)
International Classes:
G06F40/237
Foreign References:
US20150309982A12015-10-29
CN106610930A2017-05-03
US20130325442A12013-12-05
CN103365838A2013-10-23
Attorney, Agent or Firm:
HANHOW INTELLECTUAL PROPERTY PARTNERS (CN)
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