838 results about "Data translation" patented technology

A real-time system for the multimodal generation of virtual reality scenes based on artificial intelligence for the creation of immersive three-dimensional environments from natural language narratives, consisting of: a speech capture module configured to continuously record a user's spoken narrative via one or more directional microphones, preprocesses the captured signal by noise reduction and temporal alignment, and outputs a digital speech stream; A speech-to-text processing unit that is operationally coupled to the speech capture module and configured for real-time speech recognition using a continuous neural transformer model. The unit is trained to transcribe natural language utterances into structured text data while maintaining contextual continuity throughout the evolving narrative. a semantic interpretation processing unit that is communicatively linked to the speech recognition unit and configured to perform natural language understanding techniques to extract contextual entities, spatial references, temporal relationships, and object attributes from the transcribed narrative; the engine includes a large language model that is fine-tuned for spatial reasoning tasks; a scene graph generation module configured to transform the interpreted semantic data into a structured, hierarchical representation that defines nodes for identified entities and edges for corresponding relationships, with each node associated with metadata describing geometry, position, orientation, texture, and linking attributes between objects; a multimodal image-language model processor coupled with the scene graph generation module, wherein the processor is configured to retrieve, adapt, or synthesize appropriate three-dimensional elements from a pre-trained visual-lexical embedding space and align these elements with their semantic and spatial definitions derived from the scene graph; a scene assembly and rendering controller configured to create a cohesive virtual scene from the aligned assets, perform real-time rendering using a GPU-accelerated ray tracing pipeline, and produce a stereoscopic visual output that corresponds to the evolving narrative; A head-mounted virtual reality visualization device connected to the rendering engine and configured to display the generated immersive environment to the user in real time. The device features motion sensors and inside-out tracking cameras to detect head and body movements, dynamically updating viewing angles and perspective within the rendered scene; and a bidirectional feedback module integrated into the head-mounted device and connected to the semantic interpretation processing unit; the module is configured to interpret corrective commands, gestures, or supplementary comments from the user to refine or modify specific scene elements without interrupting the real-time visualization; The system continuously updates the virtual scene as the narrative develops, ensuring temporal synchronization between speech input and rendered output below a defined latency threshold, thus enabling a natural, dialogic construction of complex three-dimensional virtual environments.

The invention provides a system for generating spatially explicit auditory cues for a recipient. It includes a processor to receive real-time location data of multiple physical entities relative to the recipient's spatial position and visual orientation. An audio generation module transforms this data into distinct audio signals using Head-Related Transfer Functions (HRTFs) to simulate perceived direction and distance. The output device, such as a headset or vehicle speakers, presents these audio signals spatially to allow perception of entities' relative locations. The system can adjust volume based on entity distance, integrate Doppler effects to indicate motion, and mute entities outside predefined distance boundaries. It also supports above-ground and ground assets, with altitude information converted to audible cues. The system monitors the recipient's orientation in real-time to adjust the HRTFs accordingly.

The invention discloses a cockpit scene recommendation method and device, a storage medium, a program product and a vehicle, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the preprocessing of man-machine conversation text data of a voice burying point log of the vehicle, obtaining the natural language description of a user, carrying out the similarity screening in a preset scene knowledge base, and obtaining a voice burying point log of the vehicle; obtaining corresponding scene knowledge; splicing the user natural language description with the scene knowledge to obtain a scene recommendation prompt word; and performing scene action reasoning on the scene recommendation prompt word through the large model agent, and outputting a scene action execution list corresponding to the scene knowledge. According to the method, man-machine conversation text data is converted into user natural language description, corresponding scene knowledge is screened, scene action reasoning is carried out based on the powerful text understanding and generating capacity of a large model agent, and the intelligent scene recommendation service of the cockpit can be automatically realized according to the voice description of a vehicle owner; and the accuracy of cabin scene recommendation is improved.

Protocol detection circuits for detecting the field device protocol of a field device attached to a channel having a data line are sequentially connected to the data line by a controller that communicates to the field device through the protocol detection circuits. The protocol detection circuits are disconnected from the field device after protocol detection is completed. The channel may be one of a number of channels; the controller may also connect and disconnect the protocol detection circuits from the one channel whereby the protocol detection circuits can be used with any channel. After the protocol of the field device is identified a protocol adapter can be inserted into the channel to enable data conversion between the field device protocol and an another protocol used by the channel for data transmission.

An apparatus and method for unpaired time series to time series translation is disclosed. The apparatus comprises at least a processor configured to receive an automated analysis of a time series, convert that time series from its initial domain to a usable time series within another user-selected domain, then to validate the conversion against a confidence threshold.

The invention discloses a power transmission line icing state detection method and system, and the method comprises the steps: obtaining an original icing image of a power transmission line, and calculating the equivalent icing thickness based on the original icing image; converting the meteorological data into a parameterized expression, and performing iterative optimization on parameters in the expression to obtain a composite correction factor; performing correction optimization on the equivalent icing thickness based on a composite correction factor to obtain a corrected icing thickness; according to the method, the preliminary equivalent icing thickness is corrected and optimized by constructing the environmental meteorological element composite correction factor, so that the icing state detection precision can be ensured in a complex environment.

A machine learning model can be run with a first input data to obtain a first output from the machine learning model. A first rule representing an interpretable explanation for the machine learning model predicting the first output can be obtained. A modified rule can be received, which changes the first rule. A transformation function can be generated, which transforms a given input data for inputting to the machine learning model to a new input data based on decision boundaries of the machine learning model and the modified rule. The first rule, the first output, the modified rule, and the transformation function can be stored in a first table.

The invention relates to an automatic switching method and system adaptive to multiple communication protocols, and the method comprises the steps: executing the wake-up operation of a controller after an instrument is powered on, and monitoring a data frame on a CAN bus; extracting a CANID (Controller Area Network Identifier) in the data frame, matching the CANID with a preset manufacturer handshake command list, and judging whether a handshake command exists or not; if the matched handshake instruction exists, determining a corresponding manufacturer communication protocol type; according to the manufacturer communication protocol type, determining a corresponding CAN message analysis method and a CAN message sending method; receiving a first CAN message, and analyzing the first CAN message by using a CAN message analysis method to generate display data; and obtaining operation data of the user, converting the operation data into a second CAN message according to the CAN message sending method, and sending the second CAN message to the controller. The application has the effect of improving the communication efficiency.

The invention belongs to the technical field of intelligent voice processing, and particularly relates to a spoken language pronunciation training and correcting system based on intelligent equipment, which acquires a user rhythm feature set including pitch change rate, accent intensity, pause duration and intonation contour by acquiring spoken language audio data sent by a user for a target text, and corrects the spoken language pronunciation training and correcting system. The method comprises the following steps: acquiring spoken language audio data, converting the spoken language audio data into a phoneme sequence aligned with target text time, generating a rhythm deviation degree report according to comparison evaluation of a user rhythm feature set and the phoneme sequence, an execution intonation mode, accent distribution, speech stream sound change and speech speed rhythm, and determining the rhythm deviation degree according to a rhythm problem type in the report in combination with user historical learning data. And forming and outputting a correction scheme including a text prompt, a targeted minimum contrast training unit and a listen-and-read simulation task, solving the problem of weak capability of correcting hyper-phoneme in a second language spoken language of an adult, and improving the authentic and fluency of the spoken language, thereby realizing efficient personalized learning.

A system and method for compression performs analysis of incoming audio or video data, and selects a manifold based on the analysis of the data. A deep learning model is then trained for the manifold. The data is broken down into components and entropy maximization algorithms are utilized for each component before compression commences. Finally, the system translates the compressed data into a standard file format.

The invention belongs to the technical field of man-machine interaction, and discloses a diagnosis and treatment auxiliary system and method based on a voice gesture interaction technology, and the system comprises a voice recognition module which is used for collecting voice information; converting the voice information into text information; inputting the text information into the large language model to obtain a voice system instruction, and sending the voice system instruction to the data processing and interaction module; the gesture recognition module is used for collecting diagnosis and treatment scene information; identifying a preset operation gesture in the diagnosis and treatment scene information; mapping a preset operation gesture into a gesture system instruction and sending the gesture system instruction to the data processing and interaction module; the data processing and interaction module is used for receiving and executing a voice system instruction or a gesture system instruction; generating a calling instruction according to the voice system instruction or the gesture system instruction and sending the calling instruction to the network communication module; converting the received medical record data into diagnosis and treatment data in a display format; the network communication module is connected with a hospital information system; the calling module is used for calling medical record data after receiving a calling instruction of the data processing and interaction module and sending the medical record data to the data processing and interaction module; the display module is used for displaying the diagnosis and treatment data. The problem that a doctor cannot conveniently operate a computer to check patient data due to the sterility principle in the diagnosis and treatment process is solved, the diagnosis and treatment efficiency is improved, infection control is facilitated, and the sterility principle is met.

An apparatus and method (200) for defining a semantic framework for a plurality of entities in a computer simulated environment. The method (200) includes receiving data from one or more data acquisition devices (104), translating, the data into one or more executable queries to extract data relating to the one or more elements from the knowledge database (106). The method (200) further includes assembling an entity model with one or more elements identified from the CNL data, each element operationalized using a model ontology and instantiating each element in the entity model using a plurality of instances for each element in the entity model to generate a semantic binding among the plurality of elements. Furthermore, the method (200) includes transforming the semantic binding into a knowledge graph using standard graph databases and translating the semantic description from the knowledge graph into an executable configuration for the metaverse.

The invention discloses a multi-dimensional constellation diagram mapping enhanced orthogonal chirp multiplexing optical transmission sending method, receiving method and system in the field of optical communication. The method comprises the following steps: a sending end converts data to be transmitted into an original signal bit stream; mapping through a preset four-dimensional constellation diagram model to generate a four-dimensional constellation point coordinate sequence, and dividing the four-dimensional constellation point coordinate sequence into two different branches; respectively carrying out OCDM modulation on the four-dimensional constellation point coordinate sequences on the two branches to generate two time domain sending signal sequences; performing power distribution and superposition on the time domain sending signal sequence to form a final sending signal; and a receiving end receives the sending signal from the channel, performs OCDM demodulation on the sending signal, recovers constellation point signals in the two branches by using a serial interference cancellation technology, and obtains an original signal bit stream through demapping of the four-dimensional constellation diagram model. According to the invention, the problems of selective fading of signal frequency and overlong CP in DD-OFDM can be solved.

The invention relates to a task response strategy generation method and device, equipment, a storage medium and a program product. The method comprises the steps of obtaining voice instruction data input by a user, wherein the voice instruction data is used for indicating a robot to execute a target task indicated by the user; converting the voice instruction data into text instruction data; according to context information corresponding to the user, the text instruction data are recognized, task instructions contained in the target task are determined, and the context information comprises historical task data meeting association conditions of the target task; according to the task instruction, response strategy data of the robot for executing the target task is determined. By adopting the method, the accuracy of the task response strategy generated by the robot can be improved.

A system and method for compression performs analysis of incoming audio or video data, and selects a manifold based on the analysis of the data. A deep learning model is then trained for the manifold. The data is broken down into components and entropy maximization algorithms are utilized for each component before compression commences. Finally, the system translates the compressed data into a standard file format.

The present invention discloses a method and device for evaluating a multi-modal large model for urban governance based on multi-level texts, comprising the following steps: obtaining the true label text of a sample picture and the output text of the multi-modal large model for urban governance; using an urban management thesaurus to segment the text into independent words and calculating the similarity score of lexical units; using the urban management thesaurus to create a bag-of-words model to convert the text data into a word frequency matrix and calculating the low-level word frequency similarity score; using a trained language model to extract semantic features with context in the text and converting them into vector representations, and calculating the semantic similarity score; using a general large language model with a formatted request with business guiding words and evaluation requirements to obtain the high-level semantic similarity score corresponding to the text; and combining the similarity scores at each level to calculate the comprehensive evaluation score of the multi-modal large model. The present invention fully considers the similarity measurement in the multi-level space of texts, improving the accuracy of evaluating the text output of the urban governance large model.

The invention relates to the technical field of maritime ship target beyond visual range monitoring, in particular to a compact type ground wave radar maritime ship track prediction method and system. AIS track data are obtained and converted into distance, speed and azimuth angles under a radar coordinate system to serve as characteristic parameters; the multi-dimensional target features which are segmented into n historical time steps through preprocessing and a sliding window serve as input of a prediction model, and the model outputs a prediction result of a future single time step; in the prediction model, each encoder layer extracts time sequence features of different depths from input features, and modeling is performed on the time sequence features by using a plurality of different attention mechanisms; and the output of the last layer of encoder passes through a linear mapping layer, and the high-dimensional time sequence representation is converted into the output prediction characteristics of the future time step. The multi-head self-attention mechanism is utilized to dynamically distribute the weights of the multi-dimensional target features, the complex association among different features is captured, the relationship among different time steps is analyzed from multiple angles, and the anti-interference capability is enhanced.

The invention relates to the technical field of text recognition, and discloses a text recognition method and system for an electric power audit service. The method comprises the following steps: acquiring and preprocessing historical data of an electric power auditing service; using an OCR technology to convert historical data into a digital sequence training set; constructing a BiLSTM model, setting an attention mechanism layer in the model, performing training evaluation on the model, and adjusting parameters based on reliable indexes to control a loss function to obtain a final model; and deploying the model in a power auditing system to realize text recognition. According to the method, the input sequence can be processed from two directions through the BiLSTM model, so that richer text information is captured, features and semanteme in the text are effectively extracted, important information of related features and semanteme is automatically concerned, irrelevant information is ignored, automatic recognition of the text and extraction of key information are achieved, and the recognition efficiency of the text is improved. And the text recognition efficiency for processing the power audit service is improved.

The invention relates to a robot teleoperation algorithm system based on motion capture equipment. The system comprises a motion capture data receiving module, a pose conversion module, a safety monitoring module and a control instruction issuing module. Teleoperation is carried out by using a mode of converting data of the motion capture equipment into a robot control instruction, the efficiency of completing a specific task by the teleoperation robot can be greatly improved, multiple control modes are realized, and an operator can more intuitively operate the robot to complete the task; meanwhile, the safety monitoring module designed in the system can ensure the safety of operators and the robot when the motion capture data is abnormal or drifts, and has high robustness. Moreover, the system can achieve the adaptation to different robots, and can reduce the adaptation development amount during hardware migration.

Beamforming communication systems with crossbar switches are provided herein. In certain embodiments, a beamforming communication system includes an antenna array partitioned into a plurality of sub-arrays, a plurality of front-end channels each operatively associated with one of the sub-arrays, a plurality of data conversion channels, and a crossbar switch electrically connected between the data conversion channels and the front-end channels. Including the crossbar switch allows for a flexible allocation of the data conversion channels to the front-end channels and subsequently to each individual antenna element in the array.

In one embodiment, a method includes receiving a natural language instruction from an interface device, receiving sensor data of a physical environment from a sensing system, converting the natural language instruction into instruction tokens and the sensor data into sensor tokens. The method further includes executing an autoregressive generative model on the instruction tokens and sensor tokens to output control tokens. The method further includes generating control commands based on the control tokens and transmitting the control commands to a robotic system. The control commands cause the robotic system to perform an action affecting the physical environment.

The invention discloses an interpretation system and method for digital government affair policies, and belongs to the field of digital government affairs, and the method specifically comprises the steps that a policy data obtaining and processing module collects latest government affair policy files from the Internet, and carries out the preprocessing through a natural language, and generates text data; the knowledge graph construction module extracts key elements of the policy according to the policy text content to construct a knowledge graph; the text representation model module converts the policy text data into numerical feature vectors; the relation modeling module defines entities and relations thereof in the knowledge graph as graph data, and constructs a graph model of the relations between the entities; the semantic understanding module performs semantic understanding on the input enterprise information and converts the information into a text sequence through feature search; the reasoning module performs reasoning according to input enterprise information and government affair policies and judges the matching degree of the enterprise information and the government affair policies; the visualization module is used for carrying out visualization display on the generated result; through cooperation of the seven modules, the government affair policy is finally interpreted.

The invention relates to the technical field of information processing and intelligent analysis, and discloses a mobile terminal information extraction system based on OCR and a local large language model, comprising an OCR recognition module used for converting input image data into text data; the text optimization and information screening module is used for optimizing text data output by the OCR, and the invention further provides a mobile terminal information extraction method based on the OCR and the local large language model, and the method comprises the following steps: S1, transmitting input image data to the OCR recognition module; and S2, carrying out image preprocessing on the image data, wherein the image preprocessing comprises denoising, enhancement and edge detection processing. By combining the OCR technology, the large language model and quantum computing acceleration, the method achieves the efficient processing of complex images and multi-modal data, optimizes the information extraction process, improves the data processing speed and accuracy, and improves the overall performance of the system.

The invention discloses a conference summary generation method and device based on a voice recognition technology, and a medium, and belongs to the technical field of voice recognition. The method comprises the following steps: segmenting collected conference audio data through a preset window to obtain a plurality of conference audio clips; performing timbre identification on any conference audio clip so as to determine spokesman information contained in any conference audio clip; segmenting and splicing the plurality of conference audio clips according to the spokesman information to obtain a plurality of speaking clips taking the spokesman information as a unit, and arranging the plurality of speaking clips according to a time sequence to obtain conference speaking data; performing voice recognition on the conference speaking data to convert the conference speaking data into a conference speaking text, the conference speaking text at least comprising the spokesman information; and performing conference feature extraction on the conference speaking text, and performing structured processing on the extracted conference features to generate a conference summary.

A robot system includes circuitry configured to: receive input sequence data representing an operation of a robot placed in a real space; input the input sequence data into a conversion language model generated by machine learning to convert the input sequence data into output sequence data, wherein the output sequence data is programming code; and control the robot to perform the operation represented by the input sequence data, based on the output sequence data.

The invention discloses an antenna structure parameter optimization method based on image translation, and the method comprises the following steps: S1, selecting a to-be-optimized structure parameter according to a basic structure of a target antenna, and determining a target electromagnetic response performance parameter; s2, performing sample generation on the selected structure parameter vector through an LHS algorithm to obtain electromagnetic response data corresponding to the structure parameter; s3, performing image data conversion on the structure parameters and the electromagnetic response data to form a data set, and training an image translation network through the data set; s4, performing image translation on the target electromagnetic response image by using the trained image translation network to obtain a corresponding structure parameter image; and S5, performing parameter extraction on the structure parameter image to obtain structure parameters of the target antenna, and completing antenna design. The method solves the problems that in the prior art, the requirement for priori knowledge of engineers is high, calculation cost and time cost are high, accuracy is insufficient, and generalization of different antenna design tasks is poor.

The invention discloses a JSD-based field distribution test method and device in a complex electromagnetic environment, a medium and equipment. The method comprises the following steps: acquiring sample data of an electromagnetic signal in a microwave reverberation chamber; the method comprises the steps of obtaining a preset zero hypothesis and a preset alternative hypothesis; converting discrete sample data into a continuous empirical probability density function through kernel density estimation; calculating the Jensen-Shannon divergence between the empirical probability density function and the probability density function of the assumed distribution as the statistical magnitude of the JSD test; if the JSD test statistic is lower than the critical value, the assumed distribution corresponding to the preset zero hypothesis is not rejected, otherwise, the assumed distribution corresponding to the preset zero hypothesis is rejected, and the alternative hypothesis is accepted. The method can recognize the distribution form of the electromagnetic field in the reverberation chamber, and solves the limitation of a conventional hypothesis testing method when the number of independent samples is small or candidate distribution is similar.

A speech recognizing system comprises: an utterance data acquiring means for acquiring real utterance data uttered by a speaker, a text converting means for converting the real utterance data into a text data, a speech synthesizing means for generating corresponding synthesis speech corresponding to the real utterance data by speech synthesizing using the text data, a conversion model generating means for generating a conversion model converting input speech into synthesis speech using the real utterance data and the corresponding synthesis speech, and a speech recognizing means for speech recognizing the synthesis speech converted using the conversion model.

The invention relates to a data security technology, and discloses a medical data trusted processing method based on an intelligent contract, which comprises the following steps: a key generation center generates system public parameters and a system master key; the data purchaser initiates a medical data transaction application to the block chain platform according to the transaction number, the medical data processing keyword and the data purchaser IP address, and deploys an intelligent contract in the block chain platform; the data purchaser and the data manager serve as two transaction parties to generate data demand features according to the smart contract; the data manager encrypts the medical data according to the data demand features to obtain encrypted medical data; the data manager performs zero-knowledge verification, and the proxy re-encryption module converts the encrypted medical data into an intermediary ciphertext and sends the intermediary ciphertext to the data purchaser; and the data purchaser decrypts the medium ciphertext to obtain the medical data. The invention further provides a system of the medical data credible processing method based on the smart contract, data privacy can be protected, and the maintenance cost of the medical data can be reduced.

Systems, devices, and methods related to a deep learning accelerator and memory are described. An integrated circuit may be configured with: a central processing unit, a deep learning accelerator configured to execute instructions with matrix operands; random access memory configured to store first instructions of an artificial neural network executable by the deep learning accelerator and second instructions of an application executable by the central processing unit; one or more connections among the random access memory, the deep learning accelerator and the central processing unit; and an input / output interface to an external peripheral bus. While the deep learning accelerator is executing the first instructions to convert sensor data according to the artificial neural network to inference results, the central processing unit may execute the application that uses inference results from the artificial neural network.