96 results about "Grammatical error" patented technology

In embodiments of the present invention improved capabilities are described for a method of grammar checking, comprising providing a first level of grammar checking through a computer-based grammar checking facility to grammar check a body of text provided by a source in order to improve the grammatical correctness of the text; providing an excerpt of the body of text containing an identified grammatical error as a result of the first level of automated grammar checking to a second level of human augmented grammar checking consisting of at least one human proofreader for review; incorporating the results of the human proofreader review to contribute to an at least one corrected version of the provided body of text; and sending the at least one corrected version back the source. The method of grammar checking may provide for automatic grammar correction and text enrichment, such as when text is entered via a computer device with input limitations.

An accurate grammar analyzer that works effectively even with error-ridden sentences input by learners, based on a context-free probabilistic statistical POST (part-of-speech tagged) parser, for a template-automation-based computer-assisted language learning system. For any keyed-in sentence, the parser finds a closest correct sentence to the keyed-in sentence from among the embedded template paths exploiting a highest similarity value, and generates a grammar tree for the correct sentence where some ambiguous words are preassigned by expert language teachers. The system marks the errors under the leaves of the grammar tree by identifying the differences between the keyed-in sentence and the grammar tree of the correct sentence as errors committed by learners. By identifying most frequently recurring grammatical errors of each student, the system sets up a learner's model, providing a unique level of contingent remediation most appropriate to each learner involved.

The invention relates to a method for automatically correcting syntax errors in an English composition based on multivariate features. The method comprises a syntax error correcting preprocessing module, a syntax error correcting model training module and a syntax error checking and correcting module, wherein the syntax error correcting preprocessing module carries out part-of-speech tagging of words, syntactic parsing of sentences and word frequency statistics of words for input training texts; the syntax error correcting model training module extracts words and part-of-speech context syntactic features thereof, words and part-of-speech structure-dependent syntactic features thereof and words and part-of-speech syntactic features thereof, calculates syntactic feature weight of words and outputs a statistical model of syntax error correcting for a part-of-speech tagging library of input words, a syntax tree structure library of sentences, a word frequency statistics library of words and a part-of-speech and syntax confusion set of words; and the syntax error checking and correcting module utilizes the statistical model of syntax error correcting and a rule model of syntax error correcting to correct syntax errors in a composition to be corrected and outputs the corrected results of the syntax errors in the English composition. The method can automatically correct eleven kinds of common English syntax errors in the English composition.

The invention relates to a Chinese grammar correcting method on the basis of an XLM (Extensible Markup Language) rule, which comprises the following steps of: determining a detected Chinese text, i.e. determining the detected Chinese text through inputting or selecting; carrying out word segmentation and labeling parties of speech, i.e. decomposing the determined detected Chinese text into words and / or phrases and respectively labeling the parties of speech for the decomposed words or / and phrases; carrying out circular detection, i.e. according to the parties of speech, characters and positional relations of the words or / and the phrases labeled with the parties of speech, matching the words or / and the phrases labeled with the parties of speech with a Chinese grammar error rule in a Chinese grammar error rule database which is established on the basis of an XML and obtaining a matching result; and displaying the matching result, i.e. displaying the matching result or a modification suggestion corresponding to the matching result. The Chinese grammar correcting method has the advantages that the database has low data capacity and is convenient to maintain; the Chinese grammar correcting method is particularly suitable for establishing the database in an open-ended mode; and the Chinese grammar correcting method has wide Chinese grammar error detection range and high accuracy.

The invention provides an English composition grammatical mistake correction method based on rules. According to the method, an English composition grammatical mistake correction model composed of an English composition preprocessing module, a rule grammatical mistake correction processing module and a grammatical mistake correction result generating module which are sequentially connected is included. After an English composition is processed through the correction model, finally article mistakes, adjective phrase mistakes, prepositional phrase mistakes, pronoun mistakes, verb tense mistakes, verb voice mistakes, irregular verb mistakes, auxiliary verb and modal verb mistakes, subject-verb disagreement mistakes, singular and plural disagreement mistakes, set structure mistakes, conjunction mistakes, word class confusion mistakes, word reuse mistakes, punctuation mark mistakes, abbreviation mistakes and sentence initial case-sensitive mistakes in the English composition can be corrected. The problem that an English composition grammatical mistake statistics correction method is not high in mistake correction precision and has fewer mistake correction types is solved.

The invention provides an automatic detection and analysis method for English composition grammar errors. According to the method, first, sentence segmentation is performed on an input English composition to be detected; next, word segmentation is performed on words in each sentence after sentence segmentation; then, spelling checking is performed on the words; after it is detected that all spellings are correct, part-of-speech tagging is performed on all the words; tagging results of the multi-tag words after tagging are corrected; the flow chart of different error instance rules is constructed; combined with the existing grammar rules and error examples, the grammar check is performed comprehensively on the sentences; finally the position where the grammatical error occurs in the composition is located, and the specific modification opinion is given. The method can locate the grammatical error position and give specific error content and solution; at the same time, the grammar rulescan be extended by modifying the error example flow chart. The method has high grammar error detection and correction capability, which can quickly detect and give a feedback of an English composition, and can be applied to a real-time environment.

The invention provides an automatic correction method and an automatic correction device for a handwritten composition, wherein the method comprises the steps of: obtaining an image of the handwrittencomposition to be revised; using a connected domain analysis algorithm and a line detection algorithm to remove interference and background lines in the image of the handwritten composition; subjecting the processed image of the handwritten composition to line segmentation, word segmentation and recognition, and obtaining the corresponding text content; segmenting the sentences in the text content, performing the part of speech analysis on each sentence to acquire the word part of each word, performing shallow syntax analysis to obtain the phrases in the sentences and the types thereof, thereby selecting a rule strategy or depth model of a specific error type to detect specific grammatical errors; for each grammatical error detected, generating a correction suggestion by synthesizing therecognition result of the error recognition model and the correction suggestion model to obtain the results of correction of the entire composition, and constructing a convolutional neural network based on the content of the composition text and the results of the correction to achieve intelligent scoring of the composition text.

An apparatus, and an associated method, detects spam and other fraudulent messages sent to a recipient station. The textual portion of a received message is analyzed to determine whether the message includes errors made by non-native language speakers when authoring a text message. A text analysis engine analyzes the text using rules sets that identify grammatical errors made by non-native language speakers, usage errors made by non-native language speakers, and other errors.

The invention discloses a Chinese grammatical error detection method and device, belonging to the information processing field. The characteristics of the method include: firstly, the input text wordsare vectorized and connected to form a text matrix; then, the mask of the importance of each component in the word vector is formed by using the circulating neural network; a text matrix is reconstructed; the context information is extracted by using the loop neural network; the error scores of each word are calculated by using feedforward neural network; the error scores are utilized to infer the wrong location. The method improves the Chinese grammar detection effect by combining the text-based word vector, and has great use values.

The invention discloses an intelligent contract code real-time debugging method based on a container. The main debugging process comprises the following steps: 1) inputting an intelligent contract code by a user; 2) the front-end system detects contract codes according to the configured rules, and feeds back the result whether the codes meet the standard or not; 3) a contract code is pulled from the Docker container, grammatical analysis is carried out, an intelligent contract is compiled, abi corresponding to the contract is acquired, and meanwhile, a compilation result and a grammatical error are fed back; 4) if the contract code is compiled successfully in the step 3), deploying the contract into a Hyperchin alliance chain; 5) if the contract code compilation in the step 3) fails, feeding back a failure result and giving a modification suggestion; and 6) if the contract is deployed successfully in the step 4), starting a debugging process of the contract code, capturing contract parameters input by the user, and returning a contract calling result. Compiling, deploying and debugging of the intelligent contract are integrated, so that the problem that debugging of the intelligentcontract code is not convenient and fast enough is solved.

The embodiment of the invention discloses a method and device for translating sentences. A specific embodiment of the method comprises the steps of obtaining a to-be-translated statement; Translatingthe to-be-translated statement to obtain a translated statement corresponding to the to-be-translated statement; And inputting the translated statement into a pre-trained grammatical error correctionmodel to obtain a correct translated statement corresponding to the translated statement, the grammatical error correction model being used for performing grammatical error correction on the statement. According to the embodiment, grammatical error correction is carried out on the translated statement by utilizing the grammatical error correction model, so that the translation accuracy is improved.

The invention provides an automatic generation method and system for a test script. After a logic expression is obtained and a mapping relationship between a decision condition and an ICD (Interface Control Document) variable is obtained, a test case set corresponding to the logic expression is generated, and the ICD variable corresponding to each decision condition in the logic expression is determined according to the mapping relationship between a decision condition and the ICD variable; and on the basis, according to the ICD variable corresponding to each decision condition in the logic expression and the test case set, generating the test script corresponding to each test case in the test case set. Obviously, an automatic test script generation scheme is realized, the generation efficiency of the test script can be effectively improved, and the introduction of manual errors including grammatical errors, semantic errors and the like can be avoided.

The invention discloses a Chinese grammar debugging method and system based on multivariate text features. The method comprises the steps: (1) carrying out vector representation on a text through a pre-training model and grammar priori knowledge to obtain a semantic feature vector and a part-of-speech feature vector, and carrying out end-to-end splicing on the part-of-speech feature vector and thesemantic feature vector to obtain a vector sequence of the text; (2) extracting a feature vector sequence of the text by using a Bi-LSTM model; (3) carrying out attention enhancement based on semantic and part-of-speech matching information on the feature vector sequence; (4) performing linear transformation on the feature vector sequence after attention enhancement to obtain a label prediction sequence; (5) carrying out information enhancement based on word order relation characteristics on the label prediction sequence; and (6) capturing the constraint information of the label prediction sequence after information enhancement, and judging a grammar error boundary position based on the constraint information. Through verification, the method shows a good error checking effect and is superior to other existing similar methods.

Provided are a grammatical error correcting system and a grammatical error correcting method using the same, and in detail, the grammatical error correcting system includes: a learning unit configured to acquire a plurality of context features according to a linguistic characteristic from a plurality of corpuses and generate a primary learning classification model and a secondary learning classification model which are references of diagnosing a grammatical error from the context features; and an executing unit configured to predict the grammatical error with respect to a corpus which is input by a learner by using the primary learning classification model, predict the grammatical error by using a primary prediction result of the grammatical error and the secondary learning classification model, and correct the grammatical error, in which the secondary learning classification model is generated by an iterative learning technique by using the plurality of context features extracted from the plurality of corpuses based on the primary prediction result.

The invention belongs to the technical field of artificial intelligence, and discloses an intelligent language learning method, system and device based on machine learning, and a medium, and the method comprises the steps: obtaining the target voice of a learner; carrying out semantic and grammar understanding on the target voice through a semantic understanding model obtained through training; performing error correction on semantic and grammar understanding results through a deep learning algorithm model obtained through training; wherein the deep learning algorithm model is trained by usinga learning experience annotation data set, and the learning experience annotation data set comprises a multi-round answer sample data set after semantic and grammar understanding and a semantic and grammar error feedback sample data set; outputting results of error correction. According to the invention, intelligent language learning can be realized, daily training and improvement of language listening and speaking ability of learners are facilitated, the learners can learn language without being limited by time and regional factors, and intelligence of language learning is truly realized.

The invention discloses a Chinese grammar error detection method and device for a word vector with text information added, belonging to the information processing field. The characteristics of the method include: firstly, vectorizing the words of the input text to form a text matrix; then, forming the text information related to each word vector by using the circulating neural network; reconstructing a text matrix; extracting the context information by using the loop neural network; then calculating the error scores of each word by using the forward neural network; using the error score to infer the wrong location. The method improves the Chinese grammar detection effect by combining the text-based word vector, and has great use values.

The invention provides a Chinese composition automatic scoring method and a teaching aid system. The method comprises: a to-be-scored composition obtaining step; a shallow feature extraction step forextracting shallow features of the to-be-scored composition; a deep semantic feature extraction step for extracting deep semantic features of the to-be-scored composition, including wrongly written character features and grammatical error features; a scoring step for combining the extracted shallow features and deep semantic features, and adopting random forest fitting to obtain a scoring result of the to-be-scored composition; and a pinyin conversion step and a theme extraction step. According to the method, shallow features and deep semantic features of the composition are combined, high scoring accuracy is achieved, an ideal evaluation result is obtained through training on small samples, and the utilization rate of the samples is effectively increased; meanwhile, the functions of wrongly written character recognition and correction, pinyin recognition and conversion, grammar error recognition and correction and the like are added, multi-dimensional information is provided as feedback guidance of user writing, and user experience is enhanced.

The invention discloses a composition processing method and system based on syntactic analysis, and the method comprises the steps: carrying out the text data preprocessing of a composition text to becorrected, and obtaining the preprocessed target text data; judging whether an error exists in a logic relation between a target statement and an adjacent statement in the target text data or not, ifyes, identifying a first abnormal statement corresponding to the target statement and the adjacent statement in the composition text to be corrected, and performing first marking on the first abnormal statement; and / or comparing the syntactic structure of the target statement in the target text data with a standard syntactic structure of a preset standard statement in a standard regular databaseto judge whether the syntactic structure of the target statement conforms to the standard syntactic structure or not; if not, identifying a second abnormal statement corresponding to the target statement in the composition text to be corrected; and the second abnormal statement is marked and corrected, so that the grammatical error in the composition can be automatically corrected, and the composition correction efficiency is improved.

The invention provides a Chinese grammar error correction method based on weakened grammar error feature representation. On the basis of a Transformer neural network used for a Chinese grammar error correction task, character feature representation and context feature representation are extracted through an encoder, and a weakening factor is obtained for learning of each character in a text to besubjected to error correction. The weakening factor can combine the character feature representation and the context feature representation extracted by the encoder through a joint equation; in the feature representation of the to-be-corrected text extracted by the encoder, the feature information of the grammar error is restrained, the negative influence of the grammar error feature information on the Chinese grammar error correction model is weakened, and the performance of the sequence-to-sequence neural network model based on Transformer in the Chinese grammar error correction task is improved.

The invention relates to a HSK composition generation method based on a subject model, which comprises the following steps of: training an LDA model to obtain a sentence and a text, a distribution ofwords and text, calculating cross entropy, selecting a sentence which is closest to a subject keyword, and then generating a text. The invention provides an HSK composition generation method based ona subject model, by training the LDA theme model, the distribution of sentences and texts, words and texts are obtained, and the sentences closest to the topic keywords are selected by calculating thecross entropy, and then the texts are generated, and the automatically generated texts have good coherence and logicality, fewer grammatical errors and fewer wrong characters, which can well fulfillthe writing task and meet the needs of practical application.

The invention relates to a text grammar error correction method fusing monolingual data, and belongs to the technical field of text error correction, and the method comprises the steps: constructing areverse grammar error generation model, and training the reverse grammar error generation model; constructing an error correction parallel sentence pair for the text containing the grammar error according to the trained reverse grammar error generation model; adopting an adversarial training reverse grammar error generation model, and distinguishing grammar error sentences from error correction parallel sentence pairs; and correcting grammar error sentences by adopting an adversarial training forward grammar error correction model. According to the method, a sampling decoding strategy is adopted in back-transfer for the first time to construct a pseudo'error-correction 'parallel sentence pair; a grammar error generation model is trained based on an adversarial learning framework, and a more real pseudo error-correction parallel corpus is constructed by using the grammar error generation model.

An input device is provided having at least a plurality of touch-sensitive back surfaces, with ability to split into several independent units, with adjustable vertical and horizontal angles between those units; a method of dividing the keys of a keyboard into interface groups; each group having a home key and associated with a finger; a method of dynamically mapping and remapping the home keys of each interface group to the coordinates of the associated fingers at their resting position, and mapping non-home keys around theft associated home keys on the touch-sensitive back surfaces; a method of calculating and remapping home keys and non-home keys when the coordinates of the fingers at the resting position shift during operation; a method of reading each activated key immediately and automatically; a method of detecting typos and grammatical errors and notifying operators using human speech or other communication methods.

The present invention relates to error detection for automatically evaluating a sentence and provides an automatic sentence evaluation device using a shallow parser to automatically evaluate a sentence, whereby a simple grammatical error and an error in sentence structure analysis are detected by generating a string of parts of speech using n-gram for a composed input sentence and parsing the generated string of parts of speech on the basis of a rule (shallow parsing) defined according to a connective relationship between adjacent parts of speech, and a corrected draft is proposed for the detected errors to thereby increase accuracy of sentence evaluation, and an error detection apparatus and method for the same.

A method, system and computer program product for checking documents using colloquialisms. Colloquialisms used in messages by users in a social network are tracked. The relationships (e.g., co-worker) between the senders and recipients of these messages are identified. A social graph is then generated to depict the relations between the users in the social network based on these identified relationships. Furthermore, usage patterns of colloquialisms (e.g., a particular colloquialism is used only with close friends as opposed to co-workers) are formulated. A rule set is generated using the social graph and formulated usage patterns. By using the rule set to check documents, documents may be more accurately checked for spelling and / or grammatical errors by taking into consideration the appropriate usage of colloquialisms based on the context (e.g., communicating with a friend). Furthermore, alternative words or phrases may be appropriately recommended based on the context using such a rule set.

The invention provides a DNS service preload starting method, preloading system and management system. Under the condition that a DNS configuration file has a grammatical error, normal start of a DNS service is ensured, the DNS service is prevented from being withdrawn due to the grammatical error of the DNS configuration file, reload of a zone and domain name due to the error of the configuration file is avoided, and it is ensured that the high-efficiency stable DNS service is output to the external. In addition, the DNS configuration file is corrected automatically according to the detected grammatical error, and performance loss caused by the grammatical error is minimized.

A method, system and computer program product for checking documents using colloquialisms. Colloquialisms used in messages by users in a social network are tracked. The relationships (e.g., co-worker) between the senders and recipients of these messages are identified. A social graph is then generated to depict the relations between the users in the social network based on these identified relationships. Furthermore, usage patterns of colloquialisms (e.g., a particular colloquialism is used only with close friends as opposed to co-workers) are formulated. A rule set is generated using the social graph and formulated usage patterns. By using the rule set to check documents, documents may be more accurately checked for spelling and / or grammatical errors by taking into consideration the appropriate usage of colloquialisms based on the context (e.g., communicating with a friend). Furthermore, alternative words or phrases may be appropriately recommended based on the context using such a rule set.

Disclosed herein are a big data based language learning device and a method for learning a language using the same. The big data based language learning device includes: a database of a server computer in which sentences in a natural language are stored, the sentences consisting of ones having a grammatical error and ones having no grammatical error; a quiz module configured to receive a grammar type and / or a subject that a user wants to study from an input device that are connected a user device either wired or wireless, or that are built into the user device, and the quiz module further configured to receive a sentence among the sentences in the natural language stored in the database, the sentence corresponds to the received grammar type and / or the subject, the sentence includes the grammatical error, and the quiz module further configured to issue the sentence as a quiz on a display of the user device; an answer sheet module configured to receive an answer to the quiz from the input device of the user device; a sentence among the sentences in the natural language stored in the database of the server computer, the sentence corresponds to the received grammar type and / or the subject and the sentence includes no grammatical error, the correction module further configured to compare the answer with the sentence including no grammatical error, and the correction module further configured to correct an error in the answer; and a learning module configured to update the database of the server computer with a training pattern consisting of the answer, a rate of correct answer for the grammar type and / or the subject, a difficulty level and an incorrect answer pattern, wherein the quiz module outputs a next quiz based on the training pattern updated in the database by the learning module and wherein the input device comprises at least one of a mouse, a touch pad, a touch screen, a keyboard, a handwriting recognizer, and a microphone.

A technology for solving inconvenience such that when executing an image forming process on the basis of PDL data using a non-standard command, the image forming process cannot be executed due to a description error of the non-standard command of the PDL data even though a description of a standard command thereof is correct is provided. An error information acquiring unit for acquiring information relating to errors occurred during the image forming process; a process restriction unit for restricting execution of the image forming process on the basis of image data from which error information is acquired when the error information is acquired by the error information acquiring unit; an error content determination unit for determining whether or not the error information acquired by the error information acquiring unit is a grammatical error relating to a predetermined extended function in a page description language; and a restriction releasing unit for releasing restriction of execution of the image forming process by the process restriction unit when the error content determination unit determines that the error information acquired by the error information acquiring unit is the grammatical error relating to the predetermined extended function are provided.