223 results about "Interaction technique" patented technology

The invention provides an intelligent data query method based on a natural language, and relates to the technical field of intelligent data processing and natural language interaction.The intelligent data query method comprises the steps that firstly, enterprise original data is subjected to standard treatment, and a standardized theme database and a data directory and index definition document are constructed; key semantics are extracted based on unstructured knowledge, and a domain knowledge vector library is fused and constructed by combining document text fragments and vector representation of a mapping relation between historical questions of a user and an SQL (Structured Query Language). And after receiving a natural language question of a user, calling a large language model to identify a task type, and distinguishing knowledge questions and answers, data query and complex analysis. Executing corresponding operations according to different types: directly retrieving a vector library by knowledge questions and answers to generate answers; extracting keywords in data query and generating a query request in combination with context; and in the complex analysis, predefined workflow is judged and executed or intelligent agent processing is called, and query or analysis requirements are output.

The invention discloses a digital human interaction system based on a web end, relates to the technical field of digital human interaction, and aims to solve the problem of accumulated dislocation of browser end digital population animation and actual audio playback caused by multiple clocks and buffer scheduling. The system comprises a visual position cooperative control module, a session initialization module, an audio track and rendering canvas binding module, a multi-domain alignment time base cluster establishment module, construction of a time base cluster containing a system reference sub-time base and a content logic sub-time base, potential candidate anchor point generation module, an optimal anchor point selection module, synchronization error calculation, and judgment of a synchronization steady state, a fine adjustment state or a lost state. An optimal anchor point is screened to adjust the animation, and a visual effect studio dynamic maintenance module and an enhancement generation module assist in out-of-step processing and parameter optimization; through cooperation of multiple modules, accurate synchronization of audio and digital human animation is realized.

The invention discloses a digital large-screen interaction method and device based on multi-agent cooperation and a medium, and relates to the technical field of digital large-screen interaction.The method comprises the steps that postures, expressions and voice data of a user are collected in real time, the attention weight is calculated in combination with spatial position information, the emotional state change rate is monitored, and the user experience is improved in combination with personal historical browsing preferences; acquiring a main interaction user, an emotional state feature and an emotional change trend; according to the main interaction user, the emotional state features and the emotional change trend, obtaining an initial confidence coefficient of the suspected interested field through a semantic understanding model; and based on the candidate guide images, identifying a user selection intention through a multi-modal fusion processing mechanism, calculating a selection probability, triggering content activation of the main interaction area and content dynamic generation of the auxiliary information area, synchronizing state information, and starting an immersive collaborative interaction process. Through three-level collaborative service configuration, the beneficial effects of improving large screen content organization efficiency and enhancing immersive interaction experience are achieved.

The invention is suitable for the technical field of intelligent door locks, and provides a voice interaction processing method, device and system, an intelligent door lock and a cloud server, and the method comprises the steps: receiving a voice instruction sent by a user, and carrying out the local recognition, so as to obtain a local recognition result and the confidence of the local recognition result; when the local recognition result is matched with the local instruction set and the confidence is high, executing a local operation corresponding to the local recognition result; otherwise, establishing a secure communication session with the cloud server based on voiceprint biological characteristics extracted from the voice instruction; sending the voice instruction to a cloud server through the secure communication session, and receiving a cloud operation instruction and / or a dynamic response text returned by the cloud server; and executing corresponding operation according to the cloud operation instruction, and / or converting the dynamic response text into voice for broadcasting through a text-to-voice engine. The intelligent door lock voice interaction system solves the problem that the real-time performance, the reliability, the safety and the interaction intellectualization are difficult to balance in the existing intelligent door lock voice interaction technology.

The invention relates to the technical field of large model interaction, in particular to a long-term and short-term memory processing system based on a large model and a vector database, and provides a scheme that short-term context memory and long-term stable memory are subjected to hierarchical management and joint retrieval by performing semantic analysis and structured modeling on user interaction contents. Under the condition that historical interaction content exists, a theme segment division and intention stack mechanism is introduced, ordered organization and step-by-step alignment of intention states in multiple rounds of conversations are achieved, and matched memory entries are obtained from a cache database and a long-term database based on query semantic representation. Furthermore, by performing normalization, situational rewriting and conflict suppression on memory entries, controllable reasoning prompt information is constructed and input to a large model to generate target output, so that the consistency, stability and controllability of a generated result are improved in a multi-round interaction and cross-session scene.

The invention provides a vision-based cross-network interaction method and system, and relates to the technical field of intelligent interaction, and the method comprises the steps: obtaining a visual interaction sequence, constructing multi-modal feature representation, achieving cross-domain semantic alignment, deconstructing visual information into a hierarchical control instruction set, and transmitting the hierarchical control instruction set to a target network environment for execution after security classification. And a bidirectional mapping relation graph is constructed to realize incremental optimization. According to the method, semantic bridging between heterogeneous networks can be established, the cross-domain control precision is improved, and meanwhile safe interaction in a network isolation environment is guaranteed.

The invention relates to the technical field of intelligent voice interaction, in particular to an AI mobile phone voice interaction method oriented to automatic marketing, which comprises the following steps of: providing a comprehensive basis for personalized marketing and improving the marketing pertinence by recognizing a user emotional state and a real-time user intention in parallel and mastering the user state; an emotion state transition network is dynamically constructed and updated, key indexes are extracted, and a user emotion change rule is analyzed, so that an interaction strategy is accurately adjusted; semantic fragments are recombined by combining emotional stability and emotional infection degree indexes, adaptive dynamic marketing verbal skill is generated, the attraction and persuasion of the verbal skill are enhanced, and the marketing effect is improved; the local NPU is utilized to synthesize emotional voices and superpose features, so that natural and vivid interaction experience is provided, and recognition of a user on marketing content is enhanced; through dynamic decision-making verbal skill strategy cross-scene switching, timely adjustment is carried out according to user changes, marketing strategy stiffness is avoided, and the marketing success rate is guaranteed.

The invention relates to the technical field of voice interaction, in particular to a dialogue type AI low-delay response control method and system based on semantic analysis. The method comprises the following steps: firstly, generating a driving intensity correlation factor of a current time window according to the change of CAN bus data; further monitoring the output of the NLU, analyzing the acoustic intonation raising characteristics, and obtaining an interaction suppression coefficient in combination with the driving intensity correlation factor; further acquiring a time pressure coefficient based on the mute duration after the user stops sounding; further comparing the interaction suppression coefficient and the time pressure coefficient of the current time window to obtain a response judgment value; further analyzing the change trend of the interaction inhibition coefficient, and updating an environment improvement flag bit; and finally, according to the driving intensity correlation factor, the environment improvement flag bit and the response decision value of the current time window, carrying out multi-level response decision control, and carrying out selective reset of an interaction state, thereby solving the problems of wrong truncation and response delay of voice interaction under dynamic driving.

The invention discloses a personalized interaction method and system based on multi-modal emotion perception, and relates to the technical field of intelligent interaction, and the method comprises the steps: collecting user historical interaction event data, and extracting interaction content features and user behavior features; obtaining interaction emotion data of the user in real time through a multi-mode sensor; fusing the interactive emotion multi-modal data to generate a dynamic emotion quantized value; generating an emotion correction factor; dynamically generating a personalized interaction strategy; and executing the interaction strategy, and collecting user response data to update a historical interaction event library. The method has the advantages that the key problem that a traditional interaction system is difficult to perceive the real-time emotional state of the user is effectively solved, a closed-loop optimization system of perception-decision-execution-feedback is constructed, and the user interaction satisfaction degree and the situation adaptive capacity of the whole system are continuously improved.

The invention discloses an intelligent voice outbound system capable of realizing automatic adjustment, and relates to the technical field of intelligent voice interaction, the system comprises a voice acquisition and preprocessing module, a voiceprint analysis and emotion recognition module, a dynamic verbal skill generation module, a verbal skill real-time optimization module and a voice synthesis and outbound module; the communication efficiency and personalized service are improved through a'generation-optimization-feedback 'closed-loop design, the system generates scene-fitting verbal skills according to customer emotions, historical records and demands, adjusts strategies according to instant feedback of customers, reduces invalid conversations, reduces customer conflicts, shortens the communication period, and meanwhile, improves the user experience. Voiceprint features are decomposed into four quantifiable dimensions, emotion is accurately recognized in combination with a combination rule, limitation of a single index is avoided, the dynamic verbal skill generation module is based on a generative adversarial network, high-quality verbal skill can be learned, the dynamic verbal skill generation module adapts to multiple scenes, customization cost is reduced, and intelligent outbound large-scale application is promoted.

The invention discloses a multi-modal driving system based on streaming big language model output, which belongs to the technical field of multi-modal interaction and comprises the following steps: a streaming big language model module receives input information and then generates a text unit sequence in a streaming manner; when each text unit is generated, a multi-dimensional emotion label sequence containing emotion types, emotion intensity values and semantic association degrees is synchronously output; the speech generation module maps the text unit sequence and the corresponding multi-dimensional emotion label sequence into speech synthesis parameters, and drives a streaming text-to-speech model to generate an emotional speech stream; the label generation module generates an expression label sequence and an action label sequence of the virtual image in real time; the emotion synchronous control module performs synchronous interpolation and coordination control by taking the time step of the text unit as a reference to generate a synchronous multi-mode driving signal; and the rendering and driving module drives the virtual image based on the signal to realize collaborative output of voice, mouth shape, expression and limb movement, and realizes synchronous presentation of multi-modal emotion expression.

The invention relates to the technical field of intelligent interaction, in particular to an interaction system based on emotion recognition, and the system comprises the steps: collecting multi-modal sensing data and environment context of a user; the feature matching module is used for constructing a first situation feature by utilizing each single-dimensional feature deviation degree obtained by calculating the current multi-modal sensing data of the user and a corresponding coupling feature deviation degree when the first situation is matched, and constructing a second situation feature when the first situation is not matched; constructing a second situational feature by using the deviation degree of each single-dimensional feature obtained by calculating the current multimode sensing data of the user; the emotion risk index calculation module is used for fusing the first situation feature or the second situation feature according to a pre-trained fusion model to obtain an emotion risk index; and the interaction module is used for triggering the interaction strategy of the corresponding level according to the relationship between the emotion risk index and the latest emotion risk threshold. In the emotion recognition process, the current situation type of the user is fused, and the accuracy of emotion recognition is greatly improved.

The invention discloses an intelligent interaction system and method based on dynamic intention recognition, and relates to the technical field of intelligent interaction.The intelligent interaction method comprises the steps that firstly, current query of a user and a context set including historical dialogues, browsing records and other information are obtained; a parallel embedding model is introduced to extract semantic features of user query and semantic features of each piece of information in a context set, and dynamic correlation weighting and screening are performed on context features through a gating network with current query as guidance, so that self-adaptive deep fusion of key context information and user query is realized; and performing intention classification inference on the basis of the semantic representation after fusion enhancement to obtain a final intention recognition result. Therefore, the problems of insufficient utilization of the context information and serious noise interference can be solved, so that the intention understanding accuracy and robustness of the system when the system processes the reference unknown query are remarkably improved.

The invention relates to the technical field of user interaction, and discloses an interpretable news recommendation method and device. According to the method, the user preference vector is obtained based on comprehensive analysis of the attributes, the long-term behaviors and the short-term behaviors of the user, so that more reliable analysis can be given from the attributes and the behaviors of the user. The semantic features of the candidate news are subjected to semantic enhancement in combination with the preset knowledge base, so that higher semantic understanding depth is achieved. The vector similarity can provide a news recommendation basis from the perspective of feature analysis, the semantic association degree can provide a news recommendation basis from the perspective of semantic analysis, the deep semantic association between the user and the news can be captured through combination of the vector similarity and the semantic association degree, and the reliability of news recommendation is finally improved. The first matching information is matched features, the second matching information is matched text descriptions, and the first matching information and the second matching information are combined with each other, so that the news recommendation thought or reason can be displayed for the user, and the news recommendation method has interpretability.

The invention relates to the technical field of artificial intelligence question and answer interaction, in particular to an agent question and answer interaction method based on a large model and generative artificial intelligence, and the method comprises the steps: screening out an information unit packet which needs to be stored in a short-term memory based on the time interval between each information unit packet and question content and the similarity of embedded vectors; obtaining the time delay of the intelligent agent at the current moment, and dynamically adjusting the capacity threshold value of the short-term memory in combination with the distribution of importance scores of all information unit packets in the short-term memory; and answering the question content based on the information unit packets stored in the working memory, the short-term memory and the long-term memory of the intelligent agent at the current moment. According to the method, the problems of long dialogue key information loss, cross-dialogue memory interruption and excessive context information in a traditional intelligent question and answer interaction method are solved, and the interaction continuity, the response speed and the question and answer interaction stability in long dialogue and cross-dialogue scenes are improved.

The invention discloses a visual language interaction method and system based on a multi-modal large model, and relates to the technical field of visual language interaction.The method comprises the steps that multi-modal data are collected and preprocessed; a multi-modal large model is constructed, a multi-modal fusion module is additionally arranged in the large model, the module adopts an attention mechanism, the large model can automatically learn the importance degree between different modal data, and effective fusion of multi-modal information is achieved; inputting the preprocessed multi-modal data into a large model, and training and optimizing the large model, so that the large model can better process the multi-modal data; and inputting multi-modal information to the large model, wherein the large model specifically executes the following operations: performing feature extraction on the multi-modal information, fusing features of different modals through a multi-modal fusion module, mining semantic association therein, generating an interactive response according to the fused features, and presenting the interactive response to a user according to a preset output form. The visual language interaction experience in different scenes can be met.

The invention relates to a vehicle interaction method and a vehicle, and belongs to the technical field of vehicle interaction, and the method comprises the steps: obtaining a language instruction of a target object, generating declarative configuration data of an interaction event, and creating a component instance; binding a static attribute of the declarative configuration data in the component instance, detecting an event type in the declarative configuration data, extracting an operation instruction and parameter information so as to register an event monitor and obtain an interaction operation of a target object, and replacing a template variable of the parameter information according to data generated by the interaction operation; and constructing an action request based on the replaced parameter information and the operation instruction, sending the action request to an action execution mechanism, and executing the action, so that an end-to-end intelligent closed loop from the natural language interaction intention of the user to the automatic execution of the vehicle function is realized, and a flexible, unified and efficient event processing framework is provided for the intelligent cabin.

The invention provides a multi-agent heterogeneous client-server collaborative voice interaction system and method, and relates to the technical field of voice interaction based on artificial intelligence. The voice interaction system aims to solve the problems that an existing voice interaction system is weak in safety, poor in compatibility, insufficient in weak network adaptability and the like. The system comprises a client and a server, and access security and dialogue continuity are guaranteed through multi-factor joint authentication and abnormal dialogue compensation; the intelligent agent capability is split into independent modules, and unified adaptation and dynamic management of the multi-source heterogeneous intelligent agents are achieved through unique identification; and through a client local cache and module decoupling fault-tolerant mechanism, the system stability in weak network and fault scenes is improved. According to the invention, agent capability abstraction, resource decoupling and end cloud collaboration are realized, a voice interaction architecture with high expansibility, high stability and strong adaptability is constructed, and the method is suitable for various application scenes such as SDK integration and multi-role accompanying chat.

The invention relates to the technical field of gesture recognition interaction, and discloses an intelligent interaction system and method based on gesture recognition. The method comprises the following steps: when an environment meets a condition, synchronously acquiring an image sequence of a gesture and depth distance field data; a hand joint point two-dimensional motion track is extracted from an image, surface deformation fluctuation information is separated from depth data, the two-dimensional motion track and the surface deformation fluctuation information are subjected to space-time registration fusion, a continuous motion track curved surface in a three-dimensional space is constructed, and then geometric topology features and dynamic change features of the continuous motion track curved surface are extracted. And inputting the fusion features into a neural network classifier subjected to incremental learning training, outputting corresponding semantic tags and confidence evaluation values, and mapping to generate a control instruction after verification. According to the method, an accurate three-dimensional dynamic model is constructed through deep fusion of multi-source data, and an incremental learning mechanism is utilized to enable the system to have online adaptive capability, so that the recognition precision of complex gestures and the long-term applicability of the system are improved.

Techniques for determining one or more expected categories of data for receipt by a skill or application and comparing the expected categories of data to user disclosed data, such as from a spoken natural language user input. The techniques include determining the spoken natural language user input is directed at an interaction with a particular skill and identifying a set of data categories registered for receipt by the skill. The techniques may further include determining if the skill solicited the disclosed data of the user input or if the user mistakenly provided the disclosed data. In some embodiments, the interaction with the skill may end if the skill is not authorized to receive the disclosed data. In some embodiments, the unsolicited disclosed data may be used to identify misunderstood or confusing requests for user input.

The invention discloses a plan curve system and method based on multi-terminal separation interactive design. The system comprises a protocol processing layer, an interface tool layer and a plan value access service layer. The protocol processing layer is used for distinguishing a plan value operation type and carrying out structured forwarding on a plan value and an instruction thereof; the interface tool layer is used for receiving and responding to operation instructions edited, inquired, stored and uploaded by a user and displaying plan value discrete points on canvas; the plan value access service layer is used for monitoring the structured instruction packet forwarded by the protocol processing layer, analyzing the instruction type, responding to the pushing and uploading module, and reading and writing a curve library and a file library in a storage medium; by designing a multi-terminal separation interaction technology, the problems of storage and uploading of daily power generation or power utilization plan curves can be efficiently and accurately solved.

The invention discloses an elder accompanying intelligent dialogue method and system based on a user portrait, and relates to the technical field of intelligent interaction, and the method comprises the steps: calculating user features based on multi-modal data, splicing the user features into a user portrait vector, generating a frame sequence from voice, calculating an interaction feature vector, constructing an interaction sequence, generating a prefix tree, and extracting all paths. Calculating a support degree, and generating a candidate mode set; extracting an intention label corresponding to each mode in the candidate mode set, generating a frequent mode set, calculating similarity, generating an associated intention label and confidence, extracting frequency features in user portrait vectors, splicing the frequency features into interest feature sub-vectors, calculating joint utility, and selecting a maximum value as an optimal intention. According to the method, through combination of the prefix tree and frequent pattern mining and interaction sequence clustering, the capability of capturing long-term interaction behavior rules of old people is enhanced, and through combination of interest utility and matching utility, the accuracy of intention inference is improved.

The invention discloses a voice interaction system optimization method based on data backflow and related equipment, and relates to the technical field of artificial intelligence and vehicle-mounted man-machine interaction, and the method comprises the steps: obtaining a user verbal skill, a first semantic slot position and a first falling domain intention, and determining a standard verbal skill in a preset standard statement library, and a second semantic slot position and a second falling domain intention corresponding to the standard verbal skill, and setting a label corresponding to the verbal skill of the user based on a preset label setting rule, the similarity, the first semantic slot position, the first falling domain intention, the second semantic intention and the second falling domain intention so as to optimize the voice interaction system. According to the method, the user verbal skill is acquired from the vehicle-mounted voice cloud log, the user verbal skill and the standard verbal skill in the standard statement library are subjected to multi-dimensional matching, the real label is set for the user verbal skill according to the matching results of different dimensions and the preset label setting rule, the real label and the user verbal skill are used as training samples for data backflow, and the user verbal skill is obtained. Therefore, the voice interaction system is optimized.

The invention discloses a software interaction system and method for promoting virtual-real fusion landing of meta universe, and belongs to the technical field of virtual-real interaction. The method is realized by pure software, and supports two modes of exchanging virtual assets for entity commodities and automatically returning the virtual assets after the entity commodities are purchased. The system accesses a digital platform through a standardized interface to complete asset verification, cancel-after-verification and voucher generation, supports delivery modes such as logistics distribution, store cancel-after-verification and offline self-pick-up, can automatically return virtual assets when purchasing entity commodities, and does not need a user to upload a voucher. The method breaks through the interaction barrier between the digital world and the physical world, is suitable for platforms such as games, movies and televisions, music and cartoons, realizes virtual-real two-way automatic intercommunication, and has high practicability and commercial value.

The invention relates to the technical field of smart wearable interaction, and discloses a smart bracelet dialogue interaction method and device based on the Internet of Things, and a medium. The method comprises the following steps: acquiring a historical dialogue data stream through a voice sensor, and extracting a voice feature vector and a semantic feature vector of each dialogue segment; dividing a dialogue mode into a steady-state dialogue mode and a dynamic dialogue mode according to the fluctuation range of the multi-period voice feature vector; establishing a steady-state reference domain based on historical voice feature vector distribution, and for a dynamic dialogue mode, constructing a dynamic reference domain in combination with an association relationship between semantics and voice feature vectors; and monitoring whether the voice feature vector of the current dialogue fragment exceeds the reference domain range of the corresponding mode in real time, if not, taking the current feature as a dialogue response generation source, and if yes, selecting a correction feature vector from the corresponding reference domain as a generation source. According to the method, accurate adaptation to different dialogue scenes is realized, the stability, accuracy and continuity of interaction are improved, and the user experience is enhanced.

The invention belongs to the technical field of software interface interaction, and provides a two-dimensional CAD (computer-aided design) software interface interaction method based on customized event distribution, which completely reserves a general keyboard operation command of CAD software which is already commonly known in the industry, so that a user can quickly work according to the existing habit and input command, and the user experience is improved. By redesigning the structural process of each function, during the use of each function, the interface options are constant and tiled on the interface, so that a user can quickly know all capabilities of the function. When specific operation is carried out, direct contact can be carried out from an interface, and the triggering step of function options is simplified. In each step, the user can select a keyboard command or click a button to push the process according to the ability level and the existing habits of the user, the problem that the working efficiency of existing CAD software and the learnability of a green hand do not coexist is solved, and meanwhile, the efficiency of an original operation mode is improved to a certain degree.

The application is suitable for the technical field of data interaction, and provides an industrial internet data interaction method and system, which comprises the following steps: reading a processing product model every interval setting time value, calling a corresponding inspection form according to the processing product model, and sending the inspection form to an inspector terminal; receiving data information input by the inspector, analyzing the data information according to the processing product model to determine corresponding inspection items of the data information, and automatically filling the data information into the inspection form; receiving item information input by the inspector, wherein the item information comprises an item number and corresponding inspection data, and automatically filling the inspection data into the inspection form; receiving a remaining item filling instruction input by the inspector, generating an inspection item filling pop-up window, receiving filling information, and automatically filling the filling information into the inspection form. In this way, the inspector does not need to carefully find each inspection item, and the application automatically fills the data information, the inspection data and the filling information into the inspection form.

The application discloses an interface interaction method and device, electronic equipment and a storage medium, and applies to the technical field of interface interaction of games. The method comprises the following steps: displaying a game picture corresponding to a game, a chat channel and an information input control in a graphical user interface; in response to a first trigger operation acting on the information input control, controlling to render and display the game picture corresponding to the game in a first display area of the graphical user interface, and to render and display a virtual keyboard for information input in a second display area of the graphical user interface; wherein the display levels of the first display area and the second display area are consistent; in response to a second trigger operation acting in the first display area, executing a corresponding game function according to the second trigger operation, and in response to a third trigger operation acting in the second display area, controlling to execute a corresponding information input function. The game interaction is not affected when chatting, and the game experience can be improved.

This invention belongs to the field of voice interaction technology, specifically relating to a low-latency interaction method and system for devices under an edge-cloud collaborative architecture. The method includes simultaneous execution steps of edge-side processing and cloud-side processing of streaming user voice. Edge-side processing generates a first intent vector, while cloud-side processing pushes voice features to a large language model for deep generation. This involves obtaining the inference prediction time and the prediction variance of the cloud-based deep generation, adjusting the initial response content based on alignment parameters, and then outputting the content immediately following the edge-side filling. This invention effectively shields cloud inference and network latency, avoids semantic conflicts and abrupt acoustic splicing, and improves the real-time performance and naturalness of edge-cloud collaborative voice interaction.

Techniques for scanning physical media on physical items and providing information about those physical items are provided. In one technique, a digital image that is generated by a mobile device and that indicates a list of ingredients in an item is identified. Text that contains the list of ingredients is identified within the digital image. It is determined whether a particular ingredient in the list of ingredients satisfies one or more criteria. In response to determining that the particular ingredient satisfies the one or more criteria, the digital image is modified by causing a portion, of the text within the digital image, that corresponds to the particular ingredient, to be highlighted while the digital image is displayed on a screen of the mobile device. In a related technique, the mobile device performs all the steps, whereas in another technique, a remote server performs one or more of the steps.