64 results about "Lexical set" patented technology

A speech recognition method comprising the steps of: storing multiple recognition models for a vocabulary set, each model distinguished from the other models in response to a Lombard characteristic, detecting at least one speaker utterance in a motor vehicle, selecting one of the multiple recognition models in response to a Lombard characteristic of the at least one speaker utterance, utilizing the selected recognition model to recognize the at least one speaker utterance; and providing a signal in response to the recognition.

The invention provides a comment analysis method based on word vectors and syntactic characteristics in the field of data analysis. The comment analysis method comprises the steps of obtaining commodity page comment data of an e-commerce website; preprocessing the acquired target data set; extracting a appendix lexical set provided by Hownet and NTU to form a basic emotion dictionary; carrying outword vector training on the obtained preprocessed data set through a Word2Vec tool; establishing a probability transfer matrix by using the semantic similarity matrix; carrying out core sentence rule-based processing on the obtained commodity comment text; carrying out preprocessing on the obtained text without the redundancy; performing part-of-speech extraction (commodity attributes, negative words, degree words and sentiment words) evaluation matching on the obtained dependency relationship pairs; combining the evaluation matching pair with an emotion dictionary, subjecting evaluation objects to appraisal value calculation and quality sorting, and finally, realizing the evaluation objects through a visual interaction interface, so that accurate, real-time, automatic and convenient processing and analysis on commodity comment data are realized, and the method can be used in an e-commerce platform.

The invention provides a test corpus generation method and device and electronic equipment. The method comprises the steps of obtaining historical test corpora on a service function point line; determining a grammatical structure and a vocabulary set corresponding to the service function points in the historical test corpus; judging whether a grammar structure white list corresponding to the service function point contains the grammar structure or not; if so, querying synonym sets in one-to-one correspondence with the vocabularies in the vocabulary set from a synonym library of the service function points; establishing a plurality of synonym phrases based on the synonym sets and the syntax structure; and respectively replacing the vocabulary set in the historical test corpus with each synonym phrase to obtain a plurality of test corpuses of the service function point. A plurality of test corpora are extended from an online real historical test corpus, so that the test corpus is greatlyenriched.

The invention relates to the technical field of intelligent decision making of artificial intelligence, and discloses a text keyword recognition method. The method comprises the steps of obtaining text information, and performing word segmentation on the text information to obtain a vocabulary set; calculating the word frequency of each vocabulary in the vocabulary set, splitting the vocabulary set to obtain a sub-vocabulary set and an association relationship among the vocabularies in the sub-vocabulary set, and obtaining a total vocabulary table with characteristic values according to the word frequency of each vocabulary in the sub-vocabulary set and the association relationship among the vocabularies; and arranging the vocabularies in the total vocabulary table according to the characteristic values, and setting the vocabularies of which the characteristic values exceed a preset characteristic threshold value as keywords. The invention also relates to a blockchain technology, and information can be stored in the blockchain node. The key degree of the vocabulary is evaluated from two dimensions of the word frequency of each vocabulary in the vocabulary set and the degree of dependence of any vocabulary in the vocabulary set by other vocabularies, so that the accuracy of obtaining the keyword capable of reflecting the core meaning of the text information is improved.

The embodiment of the invention provides a method and device for extracting data in medical information, equipment and a storage medium. The method comprises the steps of determining a positioning word of the medical information; generating an adjacent vocabulary set corresponding to the positioning word based on the position of the positioning word in the medical information, wherein the adjacent vocabulary set comprises vocabularies in the medical information, and the vocabularies and the positioning word are located within a set distance; extracting target data having a specified attachment relationship with the positioning word from the adjacent vocabulary set by using a data extraction rule pre-configured for the positioning word; and positioning and extracting target data by using the positioning word and the data extraction rule pre-configured by the positioning word so as to realize extraction of specified data in different medical data.

A cloud-based vocabulary learning system includes a cloud database and a learning server. The cloud database stores multiple vocabulary sets associated with different levels, and is connected with the learning server. The learning server includes a processor and a memory. The processor executes instructions stored on the memory to receive a user level from a client device. One of the vocabulary sets is selected as, a user vocabulary set according to the user level, and an electronic document is compared with the user vocabulary set to extract new words in the electronic document. The new words are provided to the client device for learning, and are added to the user vocabulary set after learning.

The embodiment of the invention provides a data processing method and device for cognitive association ability training. The method comprises: establishing a database in advance, wherein the database comprises different types of original keywords, identifying the attributes of the original keywords, and putting the original keywords with the same attributes into the same vocabulary set to form a plurality of vocabulary sets; randomly extracting an original keyword A1 and an original keyword A2 in the same vocabulary set, and collecting a plurality of associated words input by a user for the original keyword A1 and the original keyword A2; summarizing a plurality of collected associated words input by the same user into an individual data set, summarizing a plurality of collected associated words input by different users into a group data set, and analyzing the individual data set and the group data set based on a big data processing technology to obtain a vocabulary reasoning knowledge network; and carrying out personalized content pushing and precise teaching guidance on the user based on the vocabulary reasoning knowledge network.

The embodiment of the invention provides an error correction dictionary construction method and device, a terminal and a computer storage medium, and the method comprises the steps: obtaining retrieval data and parallel corpora corresponding to the retrieval data; expanding the retrieval data and the parallel corpus to obtain a retrieval vocabulary set and a corpus vocabulary set; querying vocabulary pairs with a mapping relationship from the retrieval vocabulary set and the corpus vocabulary set; and constructing an error correction dictionary corresponding to the retrieval data according tothe vocabulary pairs. By adopting the embodiment of the invention, the problems of fewer vocabulary pairs, lower construction efficiency and the like in an error correction dictionary in the prior artcan be solved.

The embodiment of the invention provides an image-text data expansion method and device and electronic equipment, and belongs to the technical field of image processing, and the method comprises the steps: carrying out the coding vectorization of vocabularies in a corpus, so as to obtain vocabulary codes corresponding to the vocabularies; clustering the vocabulary codes to obtain a plurality of word aggregation class sets; obtaining an image set corresponding to each word aggregation class set in the plurality of word aggregation class sets; rejecting unqualified vocabulary sets according to the image distribution condition in the image set to obtain qualified vocabulary sets; and combining any element in the qualified vocabulary set with any element in the image set to obtain expanded image-text data. By means of the processing scheme, the number of high-confidence image-text data is increased, the problem that weak label data related to images and texts is insufficient is solved, andthe data collected through the scheme can be used for subsequent model training, data analysis, algorithm adjustment and other links.

The invention discloses a data processing method and a device, which determine the vocabulary set corresponding to the authority in a service system by the result of segmenting the text content in theauthority. Then through the classification of each word and determine the word frequency of each type of vocabulary in each permission, determine the attributes of the permission. Finally, the permissions of attributes are determined as training samples, and the classification model is trained to determine the types of permissions in the business system according to the classification model.

The invention provides a text information processing method and system, and the method comprises the steps: carrying out the word segmentation of a to-be-approved text, and obtaining a vocabulary setcomprising a plurality of vocabularies; extracting features of each vocabulary in the vocabulary set to obtain a vocabulary feature set; inputting the vocabulary feature set into a preset classification model for vocabulary classification, and determining whether the to-be-approved text contains sensitive words or not; if the sensitive words are contained, outputting text information used for indicating that the to-be-approved text does not pass the approval; and if the sensitive words are not included, outputting text information used for indicating that the to-be-approved text passes approval. According to the scheme, vocabulary classification is carried out on the to-be-approved text by utilizing the pre-trained classification model, and whether the to-be-approved text contains the sensitive words or not is determined. And outputting text information used for indicating whether the approval text passes approval or not according to the determination result without manual approval, sothat manpower and approval cost are saved, and approval speed and approval efficiency are improved.

The invention relates to a dictionary-based word vector generation method and system, and the method comprises the steps: enabling vocabularies contained in the dictionary to form a vocabulary set, carrying out the statistics of the occurrence frequency of each vocabulary in the vocabulary set in vocabulary paraphrases contained in the dictionary, carrying out the word segmentation of each vocabulary paraphrase according to the frequency, and obtaining a paraphrase vocabulary sequence; taking the vocabularies as nodes, connecting the nodes according to the corresponding relation between the vocabularies and the paraphrasing vocabulary sequences to form directed edges, and determining the weight of each directed edge to obtain a directed graph based on a dictionary; and calculating the directed graph based on a depth walk algorithm to obtain a word vector. According to the method, the vocabulary information provided by the dictionary is fused into the word vector, so that a high-qualitydata basis can be provided for word vector training, word meanings can be better mined, and a natural language processing task is supported.

The invention discloses a method for screening a security subset of a security-critical software modeling language. The method comprises the following steps: (1) establishing a complete vocabulary setof the modeling language; (2) removing unsafe elements from the complete vocabulary set, and establishing a preliminary screening version of a safe subset; (3) establishing a target domain programming element set; (4) carrying out adequacy analysis of the security subsets; and (5) carrying out safety verification of the safety subset. The method provided by the invention ensures the sufficiency,necessity and security of the security subset, so that the security subset not only can meet the requirements of security critical software development, but also avoids the problems caused by repeatedelement functions in the security subset, thereby generating a modeling language with extremely high security.

The invention relates to the field of audio recognition, and in particular, relates to a voice tag judgment method and system, a storage medium and electronic equipment. The method comprises the steps: acquiring open source vocabularies to form an open source vocabulary set; performing word segmentation processing on the text in the related scene to obtain a word segmentation set; obtaining an audio file, and processing the audio file to obtain a high-frequency vocabulary set; obtaining a preset list, and processing the preset list to obtain a related vocabulary set; performing union processing on the open source vocabulary set, the word segmentation set, the high-frequency vocabulary set and the related vocabulary set, and obtaining a vocabulary list; and performing tag processing on the voice content according to the vocabulary list. The method is high in operability and suitable for the cold start stage; and the ASR recognition accuracy in the content risk control field and the downstream nlp classification task and tag effect can be effectively improved, and the method can be quickly applied to related fields.

The invention relates to a multilingual speech recognition and theme semantic analysis method, which comprises the following steps: acquiring a pinyin character string corresponding to a speech input signal according to a speech comparison table, judging that the pinyin character string corresponds to a plurality of original words according to multilingual word collection, and forming a statement according to the multi-word collection and the plurality of original words through a speech recognizer; executing the following steps through a semantic analyzer: selectively executing a correction process, executing an analysis state judgment process or outputting the statement according to the statement and subject vocabulary semantic relationship data set; outputting the corrected statement when the correction process is judged to be successful, and when the correction process is judged to be failed, executing an analysis state judgment process to selectively output a judgment result.