120 results about "Word recognition" patented technology

The invention discloses a marketing mobile terminal dynamic behavior compliance monitoring method and system, belongs to the technical field of information transmission monitoring, and aims to solve the problems that existing monitoring is insufficient in non-text information processing, redundant in sensitive word judgment, incomplete in violation expression variant coverage and low in data reuse rate. The method comprises the steps that dynamic behavior information is captured, a composite retrieval code retrieval history library is constructed, and whether sensitive word recognition is conducted or not is judged; if not, generating a standardized word segmentation sequence; comparing the segmented words to determine matched segmented words and unmatched segmented words, calling a historical synonym set of the matched segmented words, positioning core semantics of the unmatched segmented words, screening evading expressions to generate a synonym set of the unmatched segmented words, and constructing a synonym data set; calling a matched word segmentation historical judgment result, establishing a synonym sequence calculation probability, and judging a sensitive word in combination with a significant proportion; executing a processing flow and updating the history library and the word segmentation library; according to the invention, efficient and accurate compliance monitoring is realized, the data reuse rate is improved, and the effectiveness of a monitoring closed loop is guaranteed.

The invention discloses a Manchu file word recognition method based on a vision-language model. The method comprises the steps of constructing an initial feature module, a stroke extraction module, a vision module, a language module, a modal alignment module and a fusion module; inputting the Manchu word picture into an initial feature extraction module to obtain an initial image feature, inputting the feature into a stroke extraction module and a visual module to obtain a stroke feature and a visual feature, inputting the visual feature into a language model, and outputting a language feature; the stroke features, the visual features and the language features are fused through a multi-mode Transform method, and a final result is controlled and output through a gating mechanism; according to the method, the recognition precision of Manchu characters with covering and staining and Manchu words with large background interference can be effectively improved.

The embodiment of the invention discloses a voice wake-up method and device, a terminal and an earphone, and belongs to the technical field of voice wake-up. The method comprises the steps that a first audio sent by an earphone is acquired, the first audio is acquired by the earphone through a first microphone and sent when a first wake-up word recognition result of the first audio represents that a wake-up word is included, and the wake-up word is used for waking up a voice interaction function of the terminal; performing voiceprint verification on the first audio to obtain a voiceprint verification result; and under the condition that the voiceprint verification result represents that the first audio passes the voiceprint verification, waking up the voice interaction function. By adopting the scheme provided by the embodiment of the invention, the probability that the voice interaction function is mistakenly awakened can be reduced.

The invention relates to a short message copywriting sensitive word recognition and analysis method based on artificial intelligence, and provides a deep semantic modeling and cross-modal semantic alignment mechanism based on multi-modal data aiming at the technical problem of realizing rich media display and text content synthesis of marketing short messages under compliance requirements. And combining the pre-trained language model and the convolutional neural network to respectively extract high-dimensional semantic features of the text and the image, and optimizing semantic consistency through an attention mechanism and a contrast loss function. Furthermore, a dynamic sensitive word recognition and avoidance strategy is introduced into the system, sensitive expressions are effectively filtered, and compliance semantic equivalence content is generated through a text reconstruction model when necessary. And finally carrying out format fusion on the content and the image to generate a rich media short message which can be sent in compliance. According to the scheme, semantic accuracy and content compliance of multi-modal information fusion are improved, it is ensured that marketing short messages meet legal compliance requirements, and the marketing short messages have good user attraction and a good transmission effect.

The invention discloses a multi-level sensitive word filtering method and system, and relates to the technical field of computers, and the multi-level sensitive word filtering method and system can comprehensively cover antagonism avoidance and semantic fuzzy scenes through a multi-level mechanism of fusion rule matching, expansion word recognition and semantic depth analysis, so that the sensitivity of a user is improved. Therefore, missed judgment and misjudgment are effectively reduced, the system adaptability is improved, missed judgment and misjudgment in the sensitive word filtering process are effectively reduced, and the adaptability and processing accuracy of the system to dynamic changes are improved.

The invention discloses an interactive hypnotherapeutic computer-implemented system based on artificial intelligence, comprising a microphone for receiving voice commands from a user; a display device for displaying dynamic pictorial representations generated by the system; a computing device operatively connected to the display device and the microphone. The computing device is configured to execute a computer program implementing a hypnotherapeutic interaction with the user based on received voice commands, whereby the computing device comprises: a word recognition module configured to recognize predefined induction words or phrases from the received voice commands; an artificial intelligence, AI, response generation module trained to respond to the recognized induction words or phrases by generating corresponding dynamic pictorial representations, created by moving particles, on the display device, and configured to record interactions and optimize responses based on user-specific feedback. The system transitions through three stages represented by distinct visual patterns of dynamic pictorial representations, induced by the predefined induction commands, wherein the dynamic pictorial representations vary in parameters defining the behavior of pictorial representation's particles, in particular vary in color and / or speed and / or movement pattern and / or scattering of representations' particles; and wherein the visual representations generated by the system are semiotically inconsistent and do not match the semantic signification of the user's voice commands. The invention also discloses a computer program product comprising instructions that cause the computer system to: a. recognize specific induction words or phrases from voice commands received via a microphone; b. in response to the recognized induction words or phrases, generate corresponding dynamic pictorial representations, comprising particles, on a display device using an artificial intelligence response generation module, the pictorial representations being distinct for three stages of the system and varying in color, speed, movement pattern and scattering of representations' particles; c. record interactions and optimize responses based on user-specific feedback; wherein the visual representations are semiotically inconsistent and do not match the semantic signification of the user's voice commands.

The application belongs to the field of natural language processing in the nuclear power industry, and particularly relates to a professional word segmentation method applied to nuclear power industry corpus, which comprises nuclear power professional vocabulary construction, nuclear power stop word vocabulary construction, nuclear power synonym vocabulary construction, nuclear power same pronoun vocabulary construction, nuclear power field new word recognition, nuclear power field entity automatic recognition, nuclear power field synonym automatic recognition, nuclear power corpus Chinese accurate word segmentation and the like operations. The application has the beneficial effect of completely solving the problem of inaccurate Chinese word segmentation of nuclear power industry corpus, laying a solid foundation for the application of subsequent big data and artificial intelligence in the field of nuclear power natural language processing, and reducing the investment of other practitioners in the field of nuclear power in natural language processing.

This invention discloses an automatic event extraction method for construction quality design specifications, comprising: acquiring and preprocessing the original specification dataset; inputting the data into a pre-trained language model for processing to obtain the event trigger word recognition results of the preprocessed dataset; employing single-trigger word and multi-trigger word classification processing methods, utilizing rule matching methods and deep learning models to jointly process multi-trigger word cases, processing the multi-trigger word recognition results of the preprocessed dataset sequentially according to colon, semicolon, and comma order, and obtaining a complete meta-event dataset using deep learning methods and similarity methods; mining the association between measurement units and measurement terms based on clustering methods, and further supplementing event semantics using similarity methods to improve event expressiveness. This invention, through a combination of grammatical matching and deep learning, completes the generation of specification inspection data, contributing to increasing the number of publicly available Chinese construction datasets.

The application discloses a trigger word recognition and positioning system and method based on BIO sequence labeling, comprising: using an encoder to extract a whole sentence semantic vector, judging whether the input text contains a backdoor attack feature; if the backdoor suspicion is detected, positioning the backdoor trigger word, judging whether each word belongs to the backdoor trigger word through the BIO sequence labeling of each token, and outputting a preliminary trigger word position marking sequence; applying trigger position prior knowledge and multi-strategy rules to correct and optimize the results and filter false positives; when the results have uncertainty or are suspected to have attack avoidance, using a predefined known trigger phrase mode library to scan the input text, capturing hidden or variant trigger word modes, and positioning the missed suspicious trigger words; and outputting the final result of backdoor detection. Through the dual-module cooperation on the architecture and the priori and rule fusion on the strategy, the application can robustly detect the text backdoor trigger and accurately position the trigger content.

The utility model discloses a Russian word recognition pronunciation recording pen, which belongs to the field of recording pens and comprises a shell, a display screen fixedly connected to one side of the shell, Russian keys arranged on one side of the shell, a circuit board fixedly connected to one side of the inner wall of the shell, and a recording module arranged on one side of the circuit board. One side of the circuit board is provided with a Russian processing module, one side of the circuit board is electrically connected with a card reader, one side of the shell is provided with a card slot, and the position of the card slot corresponds to the position of the card reader. Through cooperation of the Russian keys, the key detection circuit, the Russian processing module and the display screen, the user can autonomously search Russian words, and standard Russian pronunciation is played through the loudspeaker, so that the Russian learning effect of the device on the user is improved.

The invention discloses an airline data grading method, device and equipment, a medium and a product. The method comprises the following steps: acquiring metadata information of an airline; wherein the metadata information comprises flight data, airport data, transportation data and personal information, and performing data grading processing on the metadata information to obtain a grading recommendation result of the metadata information; wherein the data grading processing comprises blood relationship traceability grading, feature model grading, sensitive word identification grading and data identification grading, the grading recommendation result is audited and confirmed by the grading recommendation result, and a final grading recommendation result of the metadata information is obtained, so that a metadata grading result library of the airline company is updated. When data sharing and opening are carried out in the aviation industry, batch confirmation of the data security sensitivity level can be automatically completed, and the manual sensitivity level confirmation cost is reduced, so that the data sensitivity level confirmation efficiency is improved, and enterprise data opening and sharing are promoted.

The invention discloses an intelligent management and control method and device for reimbursement applications, equipment and a medium. The method comprises the following steps: according to main table information filled in a reimbursement platform by a user, if it is determined that an attachment verification condition is met, carrying out text information extraction and validity verification on an attachment uploaded by the user; performing sensitive word recognition on the attachment according to the extracted attachment text information and a pre-established sensitive word bank, and determining sensitive words in the attachment and a restricted word bank to which each sensitive word belongs; and according to the restricted word bank to which each sensitive word belongs and a preset attachment verification rule, determining a management and control operation and prompt information for the current reimbursement application, restricting the user to submit the current reimbursement application according to the management and control operation, and displaying the prompt information to the user side. By adopting the technical scheme, the reimbursement application of the user can be comprehensively monitored, and the reimbursement compliance can be accurately identified based on the attachment, so that the risk of illegal reimbursement is reduced.

The present invention discloses a method and system for jointly extracting events and event relationships based on dynamic graph propagation. The present invention constructs a multi-level dynamic graph structure and introduces a gate mechanism to realize the dynamic transmission and joint update of information between event internal elements and events, thereby realizing end-to-end collaborative learning of subtasks such as event trigger word recognition, argument recognition, role classification, event type determination and event relationship classification. The present invention simultaneously completes the prediction of event elements, event types and event relationships through dynamic graph propagation, effectively captures contextual dependencies, and has significant advantages in processing nested events and long-distance event relationships. It effectively improves the overall robustness and structural modeling capabilities of the event extraction system and can be widely used in financial public opinion analysis, medical event tracking, judicial case reasoning and other fields.

The present invention relates to the field of voice wake-up technology, and provides a voice wake-up method, device, and system with a dual protection mechanism, including: a playback device superimposes interference audio onto original audio to obtain superimposed audio, then performs wake-up word recognition on the original audio or superimposed audio, obtains a wake-up word interference mark, and sends it to a voice service server; a voice wake-up device monitors ambient sound, performs noise processing on sounds carrying interference audio to obtain pure audio, then performs wake-up word recognition on the pure audio, and when a wake-up word is recognized, generates a wake-up word arbitration and sends it to a voice service server; the voice service server matches the wake-up word interference mark with the wake-up word arbitration, detects whether there is a false triggering of the wake-up word, and generates a detection result, and the voice wake-up device executes a wake-up word response or cancels the wake-up word response based on the detection result. The present invention can reduce interference from external strong sound source devices and avoid false triggering of wake-up words.

The application discloses a kind of natural gas marketing strategy execution situation automatic early warning method and system, the method includes: S1: obtaining the natural gas marketing strategy file of a month, and the key word recognition is carried out to natural gas marketing strategy file, extracts natural gas basic data, and it is imported into audit informationization supervision and management platform marketing audit system;S2: obtaining natural gas enterprise financial management system Fmis, marketing system push natural gas system data;S3: according to the natural gas basic data and natural gas system data obtained, using natural gas marketing strategy logic calculation model, real-time calculation natural gas marketing income related quantity;S4: according to natural gas marketing income related quantity, using natural gas sales strategy execution situation suspiciousness multistage screening filtering model is checked gradually, obtains each level suspicious clue, carries out hierarchical classification automatic early warning, fills the blank of domestic about natural gas marketing intelligent audit.

The invention discloses a trigger word recognition and positioning system and method based on BIO sequence tagging, and the method comprises the steps: extracting a whole sentence semantic vector through an encoder, and judging whether an input text contains backdoor attack features or not; if backdoor suspicion is detected, backdoor trigger word positioning is carried out, whether each word belongs to a backdoor trigger word or not is judged through token-by-token BIO sequence labeling, and a preliminary trigger word position labeling sequence is output; performing result correction and optimization by applying trigger position priori knowledge and a multi-strategy rule, and filtering false alarms; when the result is uncertain or suspected to have attack avoidance, scanning the input text by using a predefined known trigger phrase pattern library, capturing a hidden or variant trigger word pattern, and positioning missed suspicious trigger words; and outputting the final fruit of the back door detection. According to the method, through dual-module cooperation on architecture and priori and rule fusion on strategy, text backdoor triggering can be detected in a robust mode, and triggering content can be accurately positioned.

The invention relates to the technical field of tourism product analysis, in particular to an elderly tourism product and experience behavior analysis management system based on big data. The user terminal obtains feedback content which is input by a user and aims at the tourism product, and then sends the feedback content to the server; the feedback content is processed to obtain text sentences corresponding to the feedback content, and the text sentences are tourism product judgment character evaluation content of the user and are subjected to sentence segmentation processing; the server carries out word recognition on the text sentences on the basis of a tourism item word bank and an emotion judgment word bank and generates an emotion score value corresponding to the feedback content, the emotion score value can reflect the evaluation degree of the user on the tourism product, the feedback content is displayed through the management terminal, and the user experience is improved. And according to the corresponding product numbers and the corresponding emotion score values, management personnel can perform targeted analysis and optimization on the tourism products according to the feedback content and the corresponding emotion score values.

The embodiment of the present application provides a low-resource end-to-end fuzzy command word modeling method and related method and device, the fuzzy command word modeling method comprises: providing a data expansion method, simulating fuzzy command word data, and improving the recognition rate of the model on the fuzzy command word. The present application simultaneously provides an end-to-end two-stage model training method, taking the class number 0 as the background voice and taking the class number c (1<=c<=C) as the command word category, wherein C represents the number of command word categories. The class number is used as a basic modeling unit, and the model is trained by using the cross-entropy criterion. The present application also provides an end-to-end decoding method, which can complete the command word segment detection without using a separate VAD model, and can complete the decoding of the command word without using a decoding network, thereby greatly reducing the memory consumption of the system.

The invention discloses a voice wake-up method, an electronic device, a storage medium and a computer program product, and relates to the technical field of signal processing, and the method comprises the steps: obtaining a sound signal, carrying out the feature extraction of the sound signal, and obtaining the two-dimensional signal features of at least two channels, the two dimensions of the two-dimensional signal features being a time dimension and a frequency dimension; the two-dimensional signal features of all the channels are subjected to convolution processing to obtain a feature map of at least one channel, the convolution processing comprises at least one time of depth separable convolution processing, and the depth separable convolution processing comprises two-dimensional depth-by-depth convolution processing and two-dimensional point-by-point convolution processing; and obtaining a voice wake-up word recognition result based on the feature map recognition of each channel. According to the method, the parameter quantity and the calculation quantity of the algorithm are greatly reduced, and the performance of end-side voice wake-up in a complex scene is improved.

The invention provides an audio wake-up method, intelligent wearable equipment and a storage medium, and the method comprises the steps: detecting the environment sound pressure in real time through a hardware voice activity detection module when an audio processing system is in a low-power-consumption monitoring state; when the environment sound pressure is greater than a preset sound pressure threshold value, the hardware voice activity detection module generates a hardware interrupt signal to trigger the logic processing module to exit a low-power-consumption monitoring state; the logic processing module executes the following steps: controlling the data carrying module to transmit audio data collected by the microphone to the shared memory module, and loading a wake-up word recognition algorithm stored in the external flash memory module to the data processing module; controlling the data processing module to operate a wake-up word recognition algorithm to recognize and process the audio data collected by the microphone in the associated time window; and when the identification processing result satisfies a preset wake-up condition, reporting a wake-up event to the application processing system. According to the technical scheme, the system power consumption is reduced, and the system response speed is increased.

Voice command recognition and natural language recognition are carried out using an accelerometer that senses signals from the vibrations of one or more bones of a user and receives no audio input. Since word recognition is made possible using solely the signal from the accelerometer from a person's bone conduction as they speak, an acoustic microphone is not needed and thus not used to collect data for word recognition. According to one embodiment, a housing contains an accelerometer and a processor, both within the same housing. The accelerometer is preferably a MEMS accelerometer which is capable of sensing the vibrations that are present in the bone of a user as the user is speaking words. A machine learning algorithm is applied to the collected data to correctly recognize words spoken by a person with significant difficulties in creating audible language.

The application discloses a sensitive word recognition method and a sensitive word tree construction method. The recognition method comprises the following steps: in step S11, a character in a text to be detected is read as a first character, and a root node of a sensitive word tree is taken as an initial parent node; in step S12, a character package value of the first character is obtained from a dictionary table, and a child node data table of the parent node is traversed in the sensitive word tree to determine a child node corresponding to the character package value of the first character; in step S13, it is judged whether the child node is a leaf node, if yes, a sensitive word is output, and step S15 is executed; if not, step S14 is executed; in step S14, a next character in the text to be detected is taken as a new first character, and the child node is taken as a new parent node, and step S12 is executed; in step S15, it is judged whether the text to be detected is completely detected, if yes, the method is ended, and if not, the method returns to step S11. The application provides a lightweight solution for quickly recognizing sensitive words.

Embodiments of the present application provide a word recognition method and device based on a speech model, electronic equipment and a medium, belonging to the technical field of financial technology. The method comprises: obtaining to-be-recognized audio and target audio; performing text conversion on the target audio to obtain hot word text corresponding to the target hot word audio; obtaining a prefix sequence of a speech model, and inputting the to-be-recognized audio and the target audio into the speech model to perform feature splicing, and outputting a spliced feature sequence; adding the target hot word audio to the spliced feature sequence to obtain a target audio sequence, and adding the hot word text to the prefix sequence to obtain a target prefix sequence; inputting the target audio sequence and the target prefix sequence into the speech model to perform hot word recognition on the to-be-recognized audio, and outputting recognized hot word audio; and performing text conversion on the to-be-recognized audio and the recognized hot word audio to obtain target audio text. The embodiments of the present application can realize accurate recognition of hot words and improve the accuracy of hot word recognition.

Embodiments regard generating a requirements statement model. A method can include extracting, from a requirements document, a requirement statement, tagging each word of the requirements statement with a corresponding part of speech tag, identifying dependencies between words and types of dependencies between each word of the requirements statement and associating types of dependencies with each word, generating respective meta-tags for each word of the requirements statement based on the part of speech tag and dependencies, each meta-tag including the parts of speech and type of dependency for each word, identifying, based on the meta-tags and the dependencies, a tree of trees that represent the structure of the requirements statement, and populating the requirements statement model that maps to the identified tree with words of the requirements statement.

This application discloses a multi-model training method, a multi-label qualitative word recognition method, and related equipment. The training method includes: selecting N target characters corresponding to N multi-label qualitative words from sample text containing multi-label qualitative words; encoding the N target characters after masking processing using a pre-trained language model of a word recognition model based on the sample text and the N multi-label qualitative words to obtain a representation vector corresponding to each target character; classifying and recognizing the N multi-label qualitative words based on each representation vector using a classifier of the word recognition model to obtain the predicted word label attributes corresponding to each multi-label qualitative word; adjusting the model parameters of the word recognition model based on the predicted word label attributes corresponding to the N multi-label qualitative words and the N sample word label attributes of the sample text, wherein the sample word label attributes are used to represent the true semantics of the corresponding multi-label qualitative words in the sample text.

The application provides a model evaluation method and device, the method comprising: identifying a preset verification set according to a sensitive word recognition model to obtain the number of true positive examples and the number of true negative examples corresponding to the sensitive word recognition model; determining a target positive example accuracy rate according to the number of true positive examples and the total number of positive examples of the verification set, and determining a target negative example accuracy rate according to the number of true negative examples and the total number of negative examples of the verification set; and performing weighted calculation on the target positive example accuracy rate and the target negative example accuracy rate to obtain evaluation information. The model evaluation method provided by the application can obtain evaluation information representing the recognition accuracy of the model by performing weighted calculation on the target positive example accuracy rate and the target negative example accuracy rate. Since the evaluation information comprehensively considers the accuracy rates of the model in positive example recognition and negative example recognition, the evaluation information can more accurately indicate the recognition accuracy of the model.

The present invention provides a universal DOC, DOCX and INDD document typesetting engine and method, which performs typesetting calculations on mainstream office documents DOC and DOCX and book publishing and magazine typesetting documents INDD, and parses the DOC, DOCX or INDD into a unified streaming document memory model through a streaming document parser; pre-processes the streaming document memory model, loads referenced documents, calculates and inserts numerical numbers of paragraphs; performs CSS format determination, word recognition, and character and word width and height calculations on the pre-processed streaming document memory model; performs page-by-page, paragraph-by-paragraph, and word-by-word calculations on the input streaming document memory model, and stores the calculation results in a layout memory document; performs subsequent processing on the typesetting calculation results to determine page number references, total number of pages, and table column calculations in the document; and converts the layout memory document into an external storage file format to achieve persistent storage of the typesetting results.

The application discloses a WAF rule evaluation method based on a regular analysis tree, relates to the technical field of WAF rule evaluation, and collects regular expression protection rules of an open source WAF as seeds, analyzes and constructs an expression library based on a regular analysis tree, then performs SQL syntax word recognition on a sent test expression, matches all related expressions in the rule expression library through SQL syntax words, traverses the sent expression request, judges whether the target site WAF protection rule is bypassed according to site feedback information, and further evaluates the rule protection capability of the target WAF system. The application can quickly and accurately deduce the target site WAF protection rule, and can reliably and accurately evaluate the protection capability of the target site WAF system.