MX2020001279A - Deep context-based grammatical error correction using artificial neural networks. - Google Patents

Deep context-based grammatical error correction using artificial neural networks.

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Publication number
MX2020001279A
MX2020001279A MX2020001279A MX2020001279A MX2020001279A MX 2020001279 A MX2020001279 A MX 2020001279A MX 2020001279 A MX2020001279 A MX 2020001279A MX 2020001279 A MX2020001279 A MX 2020001279A MX 2020001279 A MX2020001279 A MX 2020001279A
Authority
MX
Mexico
Prior art keywords
grammatical error
artificial neural
error correction
neural networks
sentence
Prior art date
Application number
MX2020001279A
Other languages
Spanish (es)
Inventor
Chuan Wang
Hui Lin
Ruobing Li
Original Assignee
Lingochamp Information Tech Shanghai Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Lingochamp Information Tech Shanghai Co Ltd filed Critical Lingochamp Information Tech Shanghai Co Ltd
Publication of MX2020001279A publication Critical patent/MX2020001279A/en

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/253—Grammatical analysis; Style critique
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/237—Lexical tools
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/205—Parsing
    • G06F40/211—Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks

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.
MX2020001279A 2017-08-03 2017-08-03 Deep context-based grammatical error correction using artificial neural networks. MX2020001279A (en)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2017/095841 WO2019024050A1 (en) 2017-08-03 2017-08-03 Deep context-based grammatical error correction using artificial neural networks

Publications (1)

Publication Number Publication Date
MX2020001279A true MX2020001279A (en) 2020-08-20

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Application Number Title Priority Date Filing Date
MX2020001279A MX2020001279A (en) 2017-08-03 2017-08-03 Deep context-based grammatical error correction using artificial neural networks.

Country Status (5)

Country Link
JP (1) JP7031101B2 (en)
KR (1) KR102490752B1 (en)
CN (1) CN111226222B (en)
MX (1) MX2020001279A (en)
WO (1) WO2019024050A1 (en)

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Also Published As

Publication number Publication date
KR102490752B1 (en) 2023-01-20
CN111226222A (en) 2020-06-02
JP2020529666A (en) 2020-10-08
CN111226222B (en) 2023-07-07
KR20200031154A (en) 2020-03-23
JP7031101B2 (en) 2022-03-08
WO2019024050A1 (en) 2019-02-07

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