95 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 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 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.

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 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 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.

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.

The invention provides a multitask learning Chinese language disease diagnosis method based on a bidirectional long-short-term memory network. The method comprises the following steps of: a Chinese level examination composition correction data set provided by a Chinese grammar error diagnosis task (CGED) in recent years is obtained; a model input sequence is obtained through fusion word embedding,text features are fully utilized, and the diagnosis effect is improved; the obtained input sequence is input into Bi-LSTM, and a Chinese grammar error diagnosis model is obtained through learning ofa neural network; a multi-task learning method is adopted, whether sentences have morbidity or not is detected as a main task, the morbidity types and error positions of the sentences are detected asauxiliary tasks, hidden layer parameters are shared among multiple tasks, and output layers related to the tasks are reserved; according to the method, the relevance between the task of detecting whether the Chinese statement has the morbidity and the task of detecting the morbidity type and the error position is fully utilized; the problem that the detection effect is poor due to the fact that nogood feature exists in the process of detecting whether the Chinese statement has the morbidity task or not is solved, and meanwhile the generalization ability of the model is improved to a certain degree due to joint optimization of multiple tasks.