12 results about "Collocation" patented technology

The invention relates to the technical field of document intelligent review, in particular to a multi-mode digital publishing intelligent review system and method based on a large model, and the system comprises a sample construction module, a multi-mode analysis module, a structure recognition module, a term verification module and an annotation output module. According to the method, a model configuration data set is generated by analyzing a subject-object combination relationship in a text and jointly screening part-of-speech, sentence pattern and semantic structure, the accuracy of semantic recognition and structure judgment is improved, and local features of semantic offset and image-text expression separation are recognized by combining a comparison relationship between an image action path and a text behavior object; a paragraph logic structure and a theme connection mode are analyzed based on semantic offset information, the problems of content dislocation and theme jump between paragraphs are effectively revealed, matching change tracks and part-of-speech continuation fluctuation in term cross-paragraph contexts are recognized, label overlapping and coverage redundancy conditions are analyzed from sentence group hierarchy, and the term cross-paragraph contexts are obtained. And forming a label combination suggestion and constructing an annotation structure record.

The application relates to the technical field of natural language processing, and discloses a Chinese numeral quantifier correction method and system, computer equipment and a storage medium. The application constructs a dynamically expandable collocation word table and a numeral dictionary; performs sentence segmentation, word segmentation and part-of-speech tagging on input text, and identifies a three-element structure composed of numerals, quantifiers and nouns; excludes misjudgments on inherent expressions through a fixed phrase filtering mechanism; performs legality verification on the structure based on the collocation word table, and generates processing information for semantic correction if the verification fails; when collocation abnormalities are confirmed and the dictionary is insufficient, a large language model is triggered to replace the quantifier and adapt to the context based on the processing information, so that a final corrected sentence is generated. Through multi-layer cooperation of rule matching, word table verification and large model verification, the application effectively reduces the mis-correction rate while ensuring high-precision correction, and improves the accuracy and practicality of automatic correction of Chinese quantifiers.

The invention provides an English word test method and system, a storage medium and electronic equipment. The method comprises the following steps: obtaining word knowledge items to be tested; the word knowledge items comprise one or more combinations of word recognition, word spelling and fixed matching complete form filling; generating test example sentences and test answers containing a preset number of word knowledge items; and feedback information of a user for the test example sentence is obtained, and whether the word knowledge item is mastered or not is determined according to the feedback information and the test answer. According to the English word testing method and system, the storage medium and the electronic equipment, whether the English words are mastered or not is accurately tested based on the specific context, and the learning efficiency and learning effect of the English words are effectively improved.

The application relates to the technical field of information retrieval, in particular to a Chinese language and literature database online query reading method and system, which comprises the following steps: extracting a word meaning item, a literature reference, a meaning length and a boundary mark, screening a candidate set, analyzing a subject pronoun and a verb collocation, positioning a paragraph and marking a word meaning item position, extracting a phrase structure comparison version offset, marking a keyword meaning number and a position, outputting a meaning, a source and a semantic path, and generating a comparison prompt; in the application, the positioning, display and structure alignment of the literature are optimized through semantic mapping, the accuracy and consistency of the target literature are improved, relevant content is accurately screened in combination with context information and version comparison, the structure offset between versions is automatically adjusted, the dependence on manual keyword setting is reduced, meanwhile, the generated word meaning comparison prompt group is optimized to improve the literature retrieval experience, the user can more quickly and accurately understand the word meaning and context relationship, and the information acquisition precision and efficiency are improved.

The invention relates to the technical field of information retrieval, in particular to an online query reading method and system for a Chinese language and literature database, which comprises the following steps: extracting word meaning items, quoting literatures, labeling paraphrase lengths and boundaries, screening candidate sets, analyzing the collocation of subject pronouns and verbs, positioning paragraphs and labeling the positions of the word meaning items, extracting phrase structures and comparing version offsets. According to the method, the positioning, the display and the structure alignment of the literature are optimized through semantic mapping, the accuracy and the consistency of the target literature are improved, and related contents are accurately screened in combination with comparison of context information and versions, so that the accuracy and the consistency of the target literature are improved. Compared with the prior art, the method has the advantages that the method is simple and easy to operate, structural deviation between versions is automatically adjusted, dependence on manual keyword setting is reduced, and meanwhile, the generated word meaning comparison prompt chunk optimizes document retrieval experience, so that a user can more quickly and accurately understand vocabulary meanings and contextual relationships, and information acquisition precision and efficiency are improved.

The application discloses a subjective question intelligent marking method and system supporting multi-text mixing, and relates to the technical field of online education. Through multi-granularity alignment and nonlinear fusion strategy, cross-paragraph information fusion and logic are effectively captured, and the scoring accuracy of complex answers is greatly improved. Combined with differentiated quality evaluation of Chinese and English, accurate scoring of Chinese coherence and structural integrity is realized, and English sentence-by-sentence fine revision can accurately mark grammatical errors and optimize vocabulary collocation. At the same time, the output of explainable scoring evidence can generate personalized comments and optimize model texts, helping students to improve accurately. The calibration mechanism and artificial review dynamically update the parameters to ensure the reliability of scoring, which not only improves the marking efficiency and reduces the human bias, but also promotes the upgrading of intelligent marking from simple scoring to accurate evaluation and personalized guidance. The problems of insufficient processing of multi-text mixed answers, lack of personalized comments and optimized model texts, and absence of English sentence-by-sentence fine revision in existing systems are effectively solved.

The invention relates to the technical field of natural language processing, in particular to a translation system for English non-fixed collocation phrases, which comprises a multi-level semantic analysis module, a distributed corpus enhancement network module, a translation strategy adaptive adjustment module, a semantic field driven context modeling module and a multi-dimensional translation quality evaluation module. The system improves the understanding ability and translation accuracy of non-fixed matching phrases in different contexts through methods of dynamic semantic mapping function, cross-language semantic map, domain feature extraction, semantic association degree calculation and the like. According to the method, the translation problem caused by semantic fuzziness, context dependency and cultural background difference can be solved, the accuracy, flexibility and cultural suitability of translation are remarkably improved, and high-quality translation service is provided for users.

The application provides a Chinese event detection method based on a part-of-speech attention mechanism, which is based on a public data set. First, the sentence is divided into words using a word segmentation tool on the data set, and then the part-of-speech sequence of the sentence is obtained using a part-of-speech tagging tool. The part-of-speech sequence of the sentence is input into a CBOW model to obtain a pre-trained part-of-speech vector, so as to learn the fixed collocation information between words, such as "suffered an injury" as a "verb + adverb + noun" structure. Then, the part-of-speech vector, the word vector and the character vector are used to extract the word-level information and the character-level information of the sentence, respectively. When extracting features, a convolutional neural network is used to extract features on the word matrix, the character matrix and the part-of-speech matrix of the sentence. Then, the part-of-speech features are used to calculate the attention score, which is used to assist the model to focus on the verb when calculating; the part-of-speech attention is provided, and after the part-of-speech features are added, the accuracy and efficiency of the model in the trigger word extraction and event type classification tasks are higher.

The application discloses a corpus expansion method, device and equipment for speech recognition and a storage medium. The method comprises the following steps: performing word segmentation on the text in the collected corpus to be expanded by using a maximum forward matching algorithm, determining the part of speech of the segmented words in the text, and determining the segmented words with the pre-marked part of speech as entities according to a preset context collocation rule; identifying the pre-built scene recognition model in the corpus to be expanded, and determining the text with two entities in the text as in-set text; establishing a child node in the parent node in the pre-built knowledge graph through in-set calculation, integrating the entities of the in-set text into the knowledge graph; and synchronizing the newly added nodes in the knowledge graph to the speech recognition model through a protocol generation rule, making the word slot effective, and serving as a speech bottom-up strategy. The corpus for speech recognition can be autonomously expanded, and the corpus expansion efficiency and precision are greatly improved.

The application discloses a construction network generation method based on word collocation analysis. The method first extracts the construction from the corpus by using a construction extraction tool based on a pre-trained model to obtain a corresponding construction library; secondly, the model fully utilizes the information of the access word of the construction through word collocation analysis, and obtains the linguistic characteristics of the construction according to the collocation strength of the access word; then, the algorithm of the pipeline hierarchical clustering is used to form the construction category and generate the first layer network; finally, the second layer and higher layer network are generated based on the construction category, and the maximum common item between the abstract degree of the construction and the construction category is taken as the feature. The method fully utilizes the construction related knowledge learned by the pre-trained model, can capture and construct the characteristics of the construction, simultaneously establishes the network relationship between the constructions, and generates the construction network.

The invention discloses a speech synthesis method and a related device, and the method comprises the steps: determining characters, the pronunciation of which needs to be adjusted, in a to-be-synthesized text, and obtaining a plurality of target words; when it is detected that polyphone characters with the same sound and character exist in the multiple target words, the multiple target words are divided into duplicate words and non-duplicate words; determining first semantic information of the duplicated words and second semantic information of the non-duplicated words according to the collocation object and sentence pattern function of each target word in the plurality of target words; according to the first semantic information and the second semantic information, semantic annotation labels of the multiple target words are determined; determining target pronunciations of polyphones in the multiple target words according to the semantic annotation labels; and generating a synthetic speech of the to-be-synthesized text according to the target pronunciation. According to the invention, accurate discrimination of pronunciation of polyphones in different contexts can be realized, and the accuracy of speech synthesis is improved.

This invention provides a method and system for essay correction based on collocation, rhetoric, and grammar. The invention constructs a conditional random field layer. The conditional random field layer is based on Markov decision chains and can reconnect the relationships between words in a sentence. After the output of the BERT encoding unit is input into the conditional random field layer, the improved Viterbi algorithm is run to decode the final grammar modification label. The output construction unit then constructs the correct sentence based on the grammar modification label.