50 results about "Data entry error" patented technology

The invention relates to the technical field of intelligent conference processing, and relates to a conference summary processing method and system using AI, and the method comprises the steps: carrying out the real-time noise suppression of a collected conference audio stream and associated text data through a noise suppression algorithm, and carrying out the cross-modal alignment of the denoised data through a cross-modal alignment algorithm; a domain-specific attention head is inserted into an attention layer of the pre-trained Transform model, a domain-enhanced speech recognition model is constructed, and audio is converted into a text sequence with a speaker tag; adopting a heterogeneous graph neural network to construct a structured topic evolution graph; key decision nodes in the structured topic evolution graph are extracted based on a reinforcement learning strategy, and a final conference summary document is generated. In the decoding stage, the fusion proportion of the acoustic model and the language model is dynamically adjusted based on the real-time acoustic confidence coefficient, the recognition rate of the vocabularies in the professional field is increased, and the problems of frequent term transcription errors and poor semantic coherence in the professional conference are effectively solved.

A method includes obtaining a set of training queries that each specify a corresponding operation to perform and include a corresponding plurality of speech recognition hypotheses that each represent a corresponding candidate transcription of the training query, and a corresponding ground-truth transcription of the training query. For each training query, the method includes processing, using an encoder of a neural semantic parsing (NSP) model, the corresponding plurality of speech recognition hypotheses to generate a corresponding NSP embedding, processing, using a transcription decoder, the corresponding NSP embedding to generate a corresponding predicted transcription, and determining a corresponding first loss based on the corresponding predicted transcription and the corresponding ground-truth transcription. The method further includes training, based on the first losses determined for the set of training queries, the NSP model to learn how to predict user intents associated with the operations specified by the training queries.

The invention relates to the technical field of project quality supervision acceptance detection, and discloses a project quality supervision acceptance detection system and method based on the Internet of Things technology, and the system comprises an information collection module, a data analysis module, a man-machine interaction module and a data storage library. The data analysis module comprises a point cloud preprocessing sub-module, a fitting comparison sub-module and a problem analysis sub-module; the man-machine interaction module comprises a quality early warning sub-module, a manual re-checking sub-module, a terminal display sub-module and a result output sub-module. According to the system, manual reading and recording are not needed, the data entry error can be reduced, and the data processing efficiency can be improved; a data analysis module automatically judges the wall surface abnormal condition and the quality excellent degree of the local point cloud model, abnormal data are verified through a man-machine interaction working mode, normal data are further mined and analyzed, and therefore the judgment accuracy and the working efficiency of the system are improved; and the workload of supervision personnel is reduced to a great extent.

The invention provides a two-process error correction method and device for real-time speech transcription, and relates to the technical field of speech processing, and the method comprises the steps: extracting the Mel spectrum features of each segment, inputting each Mel spectrum feature into a lightweight end-to-end model, and obtaining a preliminary transcription text; splicing the segments according to a preset number to obtain a plurality of long segments, and inputting each long segment into a speech recognition model to obtain a high-precision transcription text; performing text comparison on the preliminary transcription text and the high-precision transcription text according to the confidence degree set of the preliminary transcription text to obtain all error vocabularies in the preliminary transcription text; and performing corresponding error correction processing on each error vocabulary in the preliminary transcription text according to the type of the error vocabulary and the high-precision transcription text to obtain a final transcription text. According to the method, through a two-process transcription error correction mechanism of the preliminary transcription text and the high-precision transcription text, transcription error accumulation is reduced on the premise that the real-time performance is not affected, and the transcription accuracy in a complex scene is improved.

The invention relates to the technical field of overseas warehouse system loading and unloading operation, in particular to an efficient intelligent warehouse loading and unloading method which comprises a loading strategy and an unloading strategy, the loading strategy comprises reference historical records, system recommendation and customer requirements, and the unloading strategy comprises a path priority principle, a storage location priority principle and other strategies. The system solves the problems that the existing logistics industry depends on manual cargo information recording and management, the efficiency is low, data input errors, cargo misplacement and cargo disorder and dispersion easily occur, the planning and utilization of the storage space are lack of intelligent means, the space is idle or the cargo accumulation is unreasonable, and the working efficiency is high. And resource waste is caused.

The invention relates to the technical field of power grid defect recognition, in particular to an Agent-based automatic power grid defect recognition system. The system comprises the following steps: acquiring real-time acquisition data, analyzing the real-time acquisition data to obtain a data analysis result, and performing tagging processing on the real-time acquisition data according to the data analysis result to obtain tag data; based on a D-S evidence theory, according to a preset historical defect graph, performing classification processing on the label data; and performing defect identification on the classified label data by utilizing a defect identification Agent, generating a defect report according to an identification result, and feeding back the defect report to an equipment maintenance system. And the classified label data directly triggers a defect identification algorithm of the corresponding Agent, so that a communication link of traditional cross-system data calling is shortened, and the defect upgrading risk caused by processing delay can be reduced. A structured report is automatically generated, a traceable decision basis is provided for an equipment maintenance system, and artificial transcription errors are reduced.

The invention provides a hospital adverse event risk identification method and system based on causal reasoning, and the method comprises the steps: responding to an operation request of a user for reporting a hospital adverse event based on the optimization of medical advice data processing and a medical quality management process in an operation risk identification scene, inputting the detailed information of the event through a formatted form, and carrying out the operation of the event. Through multi-node, multi-auditor and multi-department cooperative auditing, an adverse event form reported by a user is subjected to approval, flow and summary analysis, medical advice data is subjected to structured storage by adopting visual enhancement OCR, dynamic knowledge graph verification and a time sequence causal reasoning model, a time window division algorithm is adopted, and medical advice data is obtained. The causal discovery algorithm constructs an unplanned re-operation association network, early warning of adverse events of operation complications is carried out, and compared with a traditional mode, the medical advice processing efficiency, the transcription error rate and the unplanned operation detection rate are all greatly improved.

A method for correcting misrecognized entity names in audio transcriptions includes receiving a transcribed utterance including dialog of a conversation and obtaining conversation context data associated with the conversation to compile a contextually relevant entity list of entities with contextual relevance to the transcribed utterance. The method further includes providing a phonetic similarity model with an input that includes the transcribed utterance and an instruction to use the contextually relevant entity list to identify specific entities phonetically similar to the transcribed utterance; and receiving, from the phonetic similarity model, an output identifying one or more entity names from the contextually relevant entity list that has been determined to satisfy a phonetic similarity metric with the transcribed utterance. The one or more entity names output by the phonetic similarity model are then used to correct a transcription error in the transcribed utterance using

The invention discloses electronic digital compass equipment, which comprises a vector sensing module, a data processing module, a trigger module, a result output module and a storage module, and is characterized in that the vector sensing module is used for acquiring original vector data required by geological survey, and ensuring the accuracy and environmental adaptability of data acquisition; the data processing module is used for receiving original data of the vector sensing module and calculating geological elements through coordinate transformation, vector operation and a calibration algorithm, the trigger module is used for controlling measurement starting time and ensuring that equipment collects data in a stable state, and the result output module is used for displaying the geological elements of a measurement surface in real time in a digital mode. The storage module is used for storing data according to a geological survey format to avoid artificial transcription errors; according to the invention, through an electronic and digital measurement mode, accurate measurement of geological elements of field geological levels or sections is realized, and the precision and efficiency of measurement of geological elements such as tendency and trend in geological survey are effectively improved.

The present invention discloses a Whisper audio transcription method, system, and storage medium based on hot word excitation. The present invention proposes a hot word framework, adds a bias encoder / decoder module to the Whisper base framework, and modifies a part of the calculation logic. Among them, the bias encoder is used to extract hot word text features, and the bias decoder combines the hot word feature excitation to transcribe the text, so that the keywords that may have been transcribed incorrectly converge in the direction of the hot word feature. Through hot word excitation, Whisper corrects the erroneous text and obtains the correct text content. Similarly, when an abnormal voice transcription occurs on site, the transcription error correction can be quickly achieved by retaining / inputting hot words, thereby optimizing the fluency of human-computer interaction.

The invention relates to a nuclear power plant instrument control important sensitive parameter management method and system. The method comprises the following steps that a production fuel management server obtains different test data from a plurality of systems and judges whether parameter modification is needed or not according to the test data; and if yes, calculating a parameter target value of the parameter to be modified according to the test data. And sending out the parameter target value when the parameter target value is confirmed to be reliable. And the instrument control important sensitive parameter management server receives the parameter target value, checks the parameter target value according to the historical database, and sends out a parameter modification task to inform the field of parameter modification when the parameter target value passes the check. And the execution result input from the terminal is received and filed, and the execution result is sent to the production fuel management server. According to the invention, full-process informatization and automation of important sensitive parameters of instrument control can be realized, human factor risks of manual mail transmission and parameter transcription errors are eliminated, and the working efficiency is improved.

An apparatus and method for correcting errors in transcribed voice commands, wherein the method comprises: receiving a voice command transcript; running a trained joint intent classification and slot filling model to generate contextualized word features and / or embeddings from word sequences detected in the transcript and subject them to intent classification and slot filling to generate predicted intent and slot value; running a trained phonetic based phrase confusion-aware model for correcting a transcription error in the predicted slot value; comparing the predicted slot value and / or an encoding or embedding generated from the predicted slot value against a plurality of predetermined valid slot values and / or a plurality of predetermined encodings or embeddings; and determining phonetic similarity scores for the predicted slot value against each valid slot value; and replacing the predicted slot value containing the transcription error with the valid slot value with highest phonetic similarity score.

The invention relates to a financial data entry error correction system, which comprises a data preprocessing module used for clearing non-printing characters in input data; the data type identification module is used for defining a data mode; the real-time verification module is used for verifying whether the amount data is a numerical value; the error prompting and correction suggestion module is used for providing error prompting and correction suggestions when error data is found; a machine learning optimization module; the expandability and usability design is realized; and the user interaction interface supports a multi-language interface and provides real-time feedback and clear operation guidance. By implementing the financial data entry error correction system, the accuracy and efficiency of data entry can be remarkably improved by a financial institution, and format errors and data omission are reduced.

The invention discloses an online car-hailing data verification method and system oriented to SaaS (Software as a Service) multiple tenants. The invention relates to the technical field of online car-hailing aggregation platform systems. User (driver or vehicle administrator) data information is input into an interface of the online car-hailing aggregation platform; the user data information comprises key fields such as an identity card number, a name, a license plate number, an engine number, a vehicle owner and a VIN code. And loading the corresponding customized verification rule according to the tenant to which the current user belongs. Performing preliminary verification on the input data, and checking whether the input data meet the specific format, length and necessary item requirements of the tenant or not; by implementing the multi-tenant customized verification rule, the unnecessary data verification process is reduced, so that the verification is more accurate and efficient. According to the automatic error correction mechanism, common data entry errors can be recognized and corrected in real time, the tedious process of manual repeated checking and modification is avoided, and the passing rate of data verification is remarkably increased.

The invention relates to the technical field of medical information technology and natural language processing, in particular to a medical science popularization live broadcast dialogue transcription method and device based on a large language model. And the final accuracy and availability of the medical science popularization live broadcast dialogue transcription can be obviously improved. According to the method, the inherent defects of a traditional ASR system in terms recognition and speaker separation in the medical industry are effectively overcome, and the word error rate and the medical concept error rate are greatly reduced, so that the medical knowledge spreading risk and the high manual calibration cost caused by transcription errors are reduced. Meanwhile, according to the scheme, complex structure modification or additional data training does not need to be carried out on a large language model, the inherent text understanding and generating capacity of the large language model is fully utilized, and efficient production and propagation of high-quality medical science popularization content are greatly promoted.

The invention discloses a budgeting method and equipment based on a business planning mode, and a medium, belongs to the technical field of business budgeting, and is used for solving the problems that a traditional budgeting mode cannot well consider fusion of data multi-dimensional attributes and flexibility of budgeting, so that the usability of budgeting is low; and the acquisition difficulty of the budget data is large, and the error probability of data entry is increased. The method comprises the steps of defining and planning a business plan grid form according to business plan compilation content; based on a budgeting requirement, carrying out usability improvement on a service plan grid form; performing budgeting on business plan compilation content through the improved business plan grid form to obtain grid form data; mapping the business plan grid form and the multi-dimensional budget form to obtain a mapping relation; and pushing the grid form data into the multi-dimensional budget data according to the mapping relationship.

A method includes obtaining a set of training queries that each specify a corresponding operation to perform and include a corresponding plurality of speech recognition hypotheses that each represent a corresponding candidate transcription of the training query, and a corresponding ground-truth transcription of the training query. For each training query, the method includes processing, using an encoder of a neural semantic parsing (NSP) model, the corresponding plurality of speech recognition hypotheses to generate a corresponding NSP embedding, processing, using a transcription decoder, the corresponding NSP embedding to generate a corresponding predicted transcription, and determining a corresponding first loss based on the corresponding predicted transcription and the corresponding ground-truth transcription. The method further includes training, based on the first losses determined for the set of training queries, the NSP model to learn how to predict user intents associated with the operations specified by the training queries.

The present invention provides a straight curve table processing method and device, and the straight curve table processing method includes: S101: receiving an input instruction, obtaining the storage format of the straight curve table according to the instruction, and reading the straight curve table according to the storage format, wherein the storage format includes the number of rows where the table header is located and the number of columns where the elements contained in the intersection stored in the straight curve table are located; S102: judging whether the transition curve corresponding to the intersection is complete, if complete, executing S104, if incomplete, executing S103; S103: reading all the pile numbers of the transition curve, and calculating the coordinates of the transition curve according to the pile numbers; S104: forming an intersection data set according to the straight curve table, and processing the intersection data set according to the input processing instruction. The present invention can obtain the storage format of the straight curve table through the input instruction, read the straight curve table according to the storage format, and process the data in the straight curve table, with high efficiency, high speed, short time consumption, and will not confuse the rows and columns of data entry, avoiding data entry errors, and improving the speed and accuracy of road design.

The invention discloses a keyword extraction method and a related device, and relates to the technical field of computers, and the keyword extraction method comprises the following steps: obtaining an original text and audio data of the original text, processing the audio data into a transliteration text through a target transliteration engine, and comparing the transliteration text with the original text to obtain a target keyword. According to the method and the device, the target transfer engine can perform real audio transfer, the target keyword with the transfer error of the target transfer engine can be extracted from the original text according to the transfer text and the original text, and the accuracy is higher. The whole process does not need manual participation, is more time-saving, labor-saving and efficient, and saves labor cost.

The invention belongs to the technical field of artificial intelligence, and discloses an artificial intelligence technology assistance-based education consultation service method, which comprises the steps of obtaining original voice data in an education consultation scene, and removing background noise through time-frequency masking processing to obtain high-quality de-noised voice data; performing character transcription on the de-noised voice data, performing adaptive text segmentation by using a pre-constructed term index database, and identifying and replacing terms which are wrongly transcribed; the method comprises the following steps of: normalizing oral statements in a text through anaphora resolution based on a context memory mechanism and an omission and completion technology based on dependency syntactic analysis; generating a preliminary scheme framework containing problem diagnosis, core suggestion and implementation steps by utilizing a large language model based on the standardized text; according to the method, the accuracy of voice recognition and the continuity of semantic understanding in education consultation can be effectively improved, and automatic and structured output of professional consultation schemes is realized.

The invention discloses a bank bill identification method and system, and the method comprises the steps: collecting an image, and carrying out the preprocessing of the image, and obtaining a preprocessed image; performing feature extraction and recognition on the preprocessed image to obtain a recognition result; performing intelligent verification and correction on the identification result to obtain correction data; and performing data output and management on the corrected data. An intelligent verification function is integrated, the consistency of bill information can be automatically compared, and data input errors are effectively prevented.

This invention relates to the field of weighing technology, and in particular to a height and weight data acquisition system based on wristband QR code recognition. The system includes a base plate, a first support column fixedly connected to the rear upper side of the base plate, a second support column rotatably connected to the upper end of the first support column via a hinge, and a mounting plate rotatably connected to the upper end of the second support column via a damping shaft. A height measurement module is installed inside the mounting plate at the end furthest from the second support column. A housing is connected to the side end of the first support column via an adjustment component, and a display screen and a QR code recognition module are fixedly connected inside the front end of the housing. A weighing module is fixedly connected to the upper upper part of the base plate. A main board is fixedly connected inside the first support column, and a data processing module, a communication module, and a power supply module are fixedly connected to the main board. This invention eliminates the need for manual intervention during the uploading of weight and height data, significantly improving the efficiency and accuracy of data acquisition and avoiding potential identity mismatches or data entry errors in traditional methods.

The invention discloses a residential land, public management and public service land soil pollution condition survey report form compiling system, which is characterized in that an account registration module generates a unique user account based on user information and land parcel codes, so that the uniqueness and traceability of data attribution are ensured, and data confusion is avoided; the first application module and the second application module respectively provide independent and collaborative operation ports, support single-user and multi-user data entry, management and calling, and significantly improve the working efficiency; the data storage module synchronously operates data in real time through the cloud, the delay risk of paper or offline data transmission is reduced, and human intervention links are reduced through a standardized process and an automatic verification mechanism, so that the data entry error rate is reduced, and the accuracy and reliability of a soil pollution assessment result are ensured; therefore, the technical problem that the accuracy of the evaluation result is affected due to the fact that the existing method not only consumes labor cost and time cost, but also easily causes data entry errors due to human factors is solved.

The application relates to the technical field of data collection management, and discloses a clinical data collection management system which comprises a data collection and integration module, a data verification and cleaning module, a safe storage and management module, a report generation and export module, a user permission and audit module and a training and support module; the data collection and integration module is responsible for collecting clinical data, supports multiple data input modes and equipment integration; the data verification and cleaning module verifies and cleans the collected data, and identifies and processes abnormal data. Through the introduction of a Bayesian network into the data collection and integration module for data consistency and correctness verification, and the use of a Kalman filtering algorithm for equipment data fusion processing, the accuracy and consistency of clinical data are effectively improved, data entry errors are reduced, and a support vector machine algorithm is used in the data verification and cleaning module for abnormal data detection.

The present application relates to the technical field of power grid defect identification, and in particular to an agent-based automated power grid defect identification system. The system comprises: acquiring real-time collected data, analyzing the real-time collected data, obtaining data analysis results, and labeling the real-time collected data according to the data analysis results to obtain label data; based on the D-S evidence theory, classifying the label data according to a preset historical defect map; using a defect identification agent to identify defects in the classified label data, and generating a defect report based on the identification results and feeding it back to the equipment maintenance system. The classified label data directly triggers the defect identification algorithm of the corresponding agent, shortening the communication link of the traditional cross-system data call, which is conducive to reducing the risk of defect escalation caused by handling delays. Automatically generate structured reports to provide a traceable decision basis for the equipment maintenance system and reduce manual transcription errors.

The utility model provides a kind of steel consumption fast measurement auxiliary device, it is related to building engineering technical field, including: operation platform, the operation platform is equipped with mounting bracket on upper side of front side;The operation platform is equipped with two clamping bases on top of rear side, the data of length and diameter measurement is calculated out single steel weight, and according to the steel quantity used in building engineering, total weight of use is quickly and accurately calculated, both avoids the error that possibly occurs when manual transcription, ensures the accuracy of data source, solves that steel consumption measurement is usually scattered as diameter measurement, length measurement, record, calculation and multiple steps such as summary, measurement personnel need to switch back and forth between measurement tool, notebook and calculator, the cumbersome operation steps increase the time of measurement to obtain final result, and frequent transcription can occur data misreading, transcription error.

The application discloses a literature metadata fusion method and system based on double-track decoupling and support degree transmission, and belongs to the technical field of data management and knowledge fusion. The application comprises the following steps: aligning literature metadata from multiple sources based on DOI to form a multi-source candidate text pool; calculating character-level similarity and semantic-level similarity of source text pairs in parallel, and extracting the difference between the two-track similarities as a decoupling feature; automatically determining the data difference into four types of consistent and reliable, transcription error, semantic rewriting or completely different according to the two-track similarities and the difference; and triggering differentiated support transmission strategies for different types. The application can effectively utilize the cognitive bias between models in the double-track architecture, identify and repair the OCR recognition errors and special symbol garbled codes that are difficult to detect by single-track models in multi-source metadata fusion, break the limitations of static priority, and significantly improve the physical purity and adaptive fault tolerance of massive multi-source academic metadata fusion.

The present invention relates to the field of intelligent conference processing technology, and relates to a conference minutes processing method and system using AI, including real-time noise suppression of collected conference audio streams and associated text data through a noise suppression algorithm, and cross-modal alignment of the noise-reduced data using a cross-modal alignment algorithm; inserting domain-specific attention heads into the attention layer of a pre-trained Transformer model to construct a domain-enhanced speech recognition model to convert audio into a text sequence with speaker labels; using a heterogeneous graph neural network to construct a structured topic evolution graph; extracting key decision nodes in the structured topic evolution graph based on a reinforcement learning strategy to generate a final conference summary document. In the decoding stage, the fusion ratio of the acoustic model and the language model is dynamically adjusted based on real-time acoustic confidence, thereby improving the recognition rate of professional vocabulary and effectively reducing the frequent transcription errors and poor semantic coherence of terminology in professional meetings.

The invention discloses an automatic testing and fault reporting system based on FCT. The automatic testing and fault reporting system comprises a central control module, a testing execution module, a data acquisition module, a data storage module, a data analysis module and a report generation and fault reporting module. The whole testing process is controlled in a coordinated mode through the central control module, automation of the whole process from testing execution, data collection, result judgment to record generation and fault declaration is achieved, manual intervention is greatly reduced, and production efficiency is improved; besides, data are automatically collected through an instrument, manual copying errors are avoided, all data are provided with timestamps and bound with specific work orders and product serial numbers, and authenticity and traceability of the data are guaranteed.

A method (300) includes obtaining training queries (210) that include a corresponding plurality of speech recognition hypotheses (211) that each represent a corresponding candidate transcription and a corresponding ground-truth transcription (214) of the training query. For each training query, the method includes processing, using an encoder (152) of a neural semantic parsing (NSP) model (150), the corresponding plurality of speech recognition hypotheses to generate a corresponding NSP embedding (153), processing, using a transcription decoder (220), the corresponding NSP embedding to generate a corresponding predicted transcription, and determining a corresponding first loss (242) based on the corresponding predicted transcription and the corresponding ground-truth transcription. The method further includes training, based on the first losses determined for the set of training queries, the NSP model to learn how to predict user intents (158) associated with the operations specified by the training queries.