664 results about "Interactive technology" patented technology

The invention discloses a voice interaction optimization method and system based on a multi-modal large model, and relates to the technical field of artificial intelligence and voice interaction, and the method comprises the steps: carrying out the voice recognition in response to the real-time voice of a user, and obtaining voice text information; according to the voice text information, combining the voice waveform of the real-time voice of the user as the input of a multi-modal recognition model, so as to judge whether the voice dialogue is interrupted and recognize the interruption intention, and obtaining a voice interruption result; obtaining a new intention of the user according to a voice interruption result, and dynamically adjusting a system response strategy to realize interaction optimization; the accuracy and comprehensiveness of interruption detection are improved through multi-modal fusion, so that the interruption intention is accurately recognized to respond to the user intention in real time, the system dialogue interaction efficiency and reliability are remarkably improved, and the defects that existing voice interruption detection is not high in detection accuracy, dynamic response of user interruption behaviors cannot be achieved, and user experience is poor are overcome. Therefore, the problems of low interaction efficiency and poor reliability of the voice dialogue system are solved.

The invention discloses a virtual-real fusion exhibition display interaction system and a multi-mode perception method, and belongs to the technical field of exhibition display interaction. The system collects audience eyeball fixation points, gesture actions and ambient light data through AR / VR equipment, analyzes coordinates of a region of interest through an eyeball fixation point attention mechanism, a gesture space-time encoder and a multi-modal fusion unit, triggers holographic projection explanation and virtual exhibition stand light and shadow dynamic adjustment (including illumination intensity, color, Gaussian blur and the like) based on a threshold value, and performs real-time display on the virtual exhibition stand. And multi-user collaborative interaction is realized through federal learning. According to the method, reinforcement learning is adopted to optimize an event-driven threshold value, and virtual and real visual splitting is eliminated in combination with ambient light adaptive mapping. The problems of low participation degree, insufficient single-mode interaction information and multi-user cooperation of traditional exhibition are solved, interest analysis accuracy is improved through multi-mode fusion, personalized experience is enhanced through dynamic interaction, the method is suitable for multiple scenes such as museums and science and technology museums, and exhibition intellectualization, immersion and group interaction efficiency are effectively improved.

The invention discloses a non-perpetual culture immersive interactive experience device and system based on a virtual digital human, and relates to the technical field of intangible cultural heritage intelligent interaction, and the device comprises a multi-mode sensing module which collects data such as user actions and voices through a depth camera and the like; the non-perpetual knowledge base module stores a non-perpetual knowledge graph and a case library; the digital human modeling engine fuses the inheritor characteristics and the user data to generate a virtual digital human; the immersion interaction engine constructs a cross-platform rendering environment to realize five-sense fusion experience; and the adaptive learning module analyzes the interaction sequence to optimize the digital human behavior, and all the modules cooperate to realize the intelligent interaction experience of non-genetic culture. Through the multi-modal perception module, the digital human modeling module and the like, the immersive interactive experience of the non-perpetual culture is realized, the user behavior can be accurately captured, the characteristic virtual digital human is generated, the five-sense fusion experience is provided, the content can be optimized based on the user interaction, the inheritance and propagation of the non-perpetual culture are promoted, and the participation degree and the sense of identity of the user are improved.

The invention provides a model-based interaction method and system, wearable equipment and a storage medium, and belongs to the technical field of intelligent interaction.The method comprises the steps that in response to a received interaction instruction, voice data, a gesture image, eye movement data and an environment image are obtained based on the interaction instruction; extracting user intention features based on the voice data, the gesture image and the eye movement data, and determining scene type features based on the environment image; determining an interaction theme based on the interaction instruction, obtaining user historical interaction information associated with the interaction theme from a context memory database, and generating a context feature vector based on the user historical interaction information; and inputting the user intention feature, the scene type feature and the context feature vector into an intention recognition model based on quantum enhancement to obtain a user intention, and generating interaction response data based on the user intention. According to the invention, the accuracy of user intention recognition can be improved, and the intelligence of interaction is improved.

The embodiment of the invention provides a digital human interaction system and method based on multi-modal emotion recognition, and belongs to the technical field of digital human interaction. The system comprises a multi-modal sensing module used for collecting multi-modal data and preprocessing the multi-modal data to generate a standardized data stream; the cross-modal fusion and emotion recognition module is used for carrying out interactive modeling on the multi-modal features and outputting a current emotion label and emotion intensity; the reaction planning module is used for generating a composite reaction strategy; and the digital human rendering module is used for mapping the composite reaction strategy into control signals corresponding to the voice, the facial expression and the action respectively, and driving a digital human to execute corresponding voice output, facial expression change and limb action through the control signals so as to realize interaction. According to the method, multi-modal data are deeply fused through the cross-modal graph neural network and comparative learning, the weight is dynamically adjusted in combination with the modal confidence, and the emotion recognition accuracy and robustness are improved.

The invention relates to the technical field of interaction based on visual earphones, and discloses an interaction method and device based on a visual earphone, computer equipment and a medium, and the method comprises the steps: judging whether a user wearing the visual earphone sends an interaction instruction or not; analyzing content in the interaction instruction to determine a user demand; in response to the user demand, controlling a camera to scan current content to obtain a scanned picture; performing data processing on the scanned picture based on the user demand to obtain a processing result; and feeding back the processing result to the user. The method has the beneficial effects that the user demand is determined through the interaction instruction, and intelligent and personalized services can be provided according to the user demand. Through the camera integrated with the earphone, a user can obtain environment information in real time without depending on external equipment, and obtain instant feedback through the earphone, so that the practicability and interaction experience of the intelligent wearable equipment in a complex environment are greatly improved.

The invention belongs to the technical field of three-dimensional scene interaction, and particularly relates to a three-dimensional immersive content interaction method and system based on 3D Gaussian spattering. The method comprises the following steps: collecting a multi-view image and carrying out motion structure recovery to obtain a camera pose matrix; according to the camera pose matrix, performing three-dimensional reconstruction processing on the image data through a 3D Gaussian spattering algorithm to obtain a reconstruction model; performing behavior analysis on the historical viewport track of the user to obtain a visual angle prediction result; and according to the visual angle prediction result and the reconstruction result of the reconstruction model, video frame generation is carried out at a client through a real-time rendering engine, and a transmission result is obtained. According to the invention, the application of the 3DGS in the three-dimensional expression technology is realized, the rendering quality is improved, and the degree of participation and immersion of the user are improved.

The invention relates to the technical field of intelligent voice interaction, in particular to an intelligent Bluetooth voice remote control system based on AI semantic analysis. Comprising a voice acquisition unit, a Bluetooth communication unit, a voice recognition unit, an AI semantic analysis unit and a control execution unit, and the Bluetooth communication unit is used for establishing low-power-consumption Bluetooth connection with target equipment and supporting bidirectional data transmission. By combining advanced localized model library, edge calculation optimization, multi-modal data fusion and dynamic semantic map technologies, the recognition accuracy, the real-time response speed and the context understanding ability of the voice instruction are remarkably improved, and meanwhile, the data privacy is guaranteed, so that efficient, personalized, natural and smooth user interaction experience is realized.

The invention discloses a virtual reality interaction method and system applied to classical famous picture display, and particularly relates to the technical field of virtual reality interaction. Multi-dimensional high-definition image acquisition and composition element three-dimensional modeling are performed on a painting, a cultural context label system is constructed in combination with historical data, a fixation point, an action posture and a staying behavior of a user are perceived in real time, accurate matching of a user behavior and a semantic label is realized, and multi-modal interaction feedback content consistent with the style of the painting is generated, so that the user experience is improved. And typical paths and misunderstanding areas are identified through clustering analysis of multi-user behavior data, and context tags and response logic are dynamically optimized, so that personalized recommendation and semantic guidance are realized, the understanding depth and immersion experience of the users on classical art are effectively improved, and the cultural expression ability and intelligent adaptability of the system are enhanced.

The invention discloses an AI digital human interactive response method based on a large language model, and relates to the technical field of digital human interaction, and the method comprises the steps: analyzing collected user voice data and visual data through a natural language processing method, generating a cross-modal feature vector, carrying out the cross-modal association analysis of the cross-modal feature vector, and carrying out the cross-modal association analysis of the cross-modal feature vector. Generating a semantic association topological graph; calculating a vertex coordinate and a joint activity threshold value of the semantic association topological graph through high-digital human correlation, inputting the vertex coordinate and the joint activity threshold value into a constructed coordinate index database to execute attention weight calibration, and outputting a multi-dimensional association graph; and performing information density analysis based on the multi-dimensional association map, generating an information density gradient vector field, and dividing a high-density core region and a low-density edge region, the high-density core region generating a semantic core coding tensor, and the low-density edge region generating an edge feature package. According to the method, the cross-modal fusion vector is converted into the cross-modal feature vector, so that the modeling of the cross-modal association relationship is realized.

The invention provides a context-based intelligent voice semantic understanding analysis method and system, and relates to the technical field of voice interaction, and the method comprises the steps: obtaining an input voice signal, extracting an acoustic feature, and decoding the acoustic feature to obtain a candidate text; constructing context semantic representation to carry out disambiguation processing; establishing a semantic dependency graph and carrying out multi-level correlation analysis; spreading context constraint information to perform multi-hop reasoning; and finally generating intention recognition and slot filling results and updating the session state. The semantic comprehension accuracy and the intelligent degree of the voice interaction system are improved by introducing the context information and the multi-level semantic dependency relationship.

The invention relates to the technical field of live broadcast interaction, in particular to an intelligent live broadcast interaction method and system based on an AI virtual human. The method comprises the following steps: identifying a real-time live broadcast interaction data stream, carrying out intelligent bullet screen filtering processing and multi-modal user interaction perception, and constructing a multi-modal user interaction perception map; key bullet screen extraction is carried out based on the multi-modal interaction perception map, and user demand prediction is carried out, so that user interaction demand features are generated; performing deep semantic space mapping on the user interaction demand features, and then performing reverse live broadcast semantic blank analysis to obtain demand blank covering information; user behavior dynamic analysis is carried out based on the multi-mode user interaction perception map, real-time interaction emotion global evolution fitting is carried out, and a real-time interaction emotion map is constructed. Through deep understanding and analysis of user demands, the emotion matching degree and the interaction content satisfaction degree of user interaction are improved.

The invention discloses an intelligent voice interaction method and device based on a voice large model, a terminal and a medium, and belongs to the technical field of voice recognition and interaction, and the method comprises the steps: recognizing the voiceprint information of a speaker through a voiceprint recognition model when a wake-up instruction is received; when the identity of the current pronunciator is the specified user registered through voiceprint, acquiring question information of the current pronunciator, calling a prompt word of a character event text of the specified user corresponding to the current pronunciator from a cloud end, and combining with a question proposed by the current pronunciator to obtain the question information of the current pronunciator; generating event text information related to a specified user character corresponding to the current pronunciator; and calling the speech synthesis model, synthesizing the generated event text information into speech according to the tone characteristics of the speaker, and outputting and playing the speech. According to the method, the user is supported to upload the character as the cue word, and the cue word is combined with the large model, so that the dialogue content generation based on the personalized information of the user is realized, and convenience is provided for the use of the user.

The embodiment of the invention provides a dialogue interaction state recognition method and system, electronic equipment and a storage medium, and relates to the technical field of voice interaction, and the method comprises the steps: extracting time sequence features and semantic features from obtained voice information; the time sequence feature represents the rhythm change condition of the user in the dialogue process, and the semantic feature represents the voice content and the voice intensity of the user in the dialogue process; recognizing the current dialogue interaction state of the user according to the time sequence features and the semantic features; the dialogue interaction state comprises one of a silent state, an interrupted state and a hesitant state. Therefore, the conversation interaction state of the user is recognized by combining the time sequence features and the semantic features, voice signal level analysis is considered, and changes of voice rhythm, voice content and voice intensity are also considered, so that the conversation interaction state of the user is accurately recognized, and the recognition precision of complex interaction states such as hesitation and interruption is improved.

The invention belongs to the technical field of computer graphics and virtual reality, and discloses a virtual-real fusion-based panoramic roaming construction method for a digital exhibition hall, which effectively solves the problems of easy drift and offset in a virtual environment in a traditional system through a multi-sensor fusion algorithm and a closed-loop optimization mechanism. Under the complex environment of people flow change, illumination fluctuation and the like in an exhibition hall, accurate alignment of virtual content and physical space can still be kept, it is ensured that a user obtains coherent and stable visual experience in the roaming process, and a reliable space reference is provided for virtual-real interaction; the light and shadow effect and the material performance of the virtual content are naturally fused with the physical environment through the physical rendering and multi-sensory interaction technology, and meanwhile, a multi-dimensional immersion sense is constructed in combination with the spatial sound effect and interaction feedback; when the user interacts with the virtual exhibit, sensory experience close to reality can be obtained, and the sense of substitution and attraction of the digital exhibition hall are remarkably improved.

The invention is applicable to the technical field of information interaction, and provides an asymptomatic patient interaction method based on an eye-controlled staring trigger communication interface, which comprises the following steps: sight tracking: acquiring facial image data of a patient through a camera, extracting facial and eye mark points, performing image processing on an eye area, and judging a staring direction; staring triggering: presetting a coordinate area of an interaction control, judging whether a fixation point of a patient falls into the control area in real time, and if the fixation point is continuously kept for preset time, triggering corresponding operation; executing a compensation mechanism: compensating head movement and illumination change in real time, and correcting a staring point coordinate; and interface design: designing an interactive interface with a daily communication function, and broadcasting the content of the control through voice. The invention provides an efficient, convenient and easy-to-use eye-controlled staring triggering communication interface for the patient with the asymptomatic disease, aims to reduce the learning cost and the operation complexity of the patient, and has great significance in improving the life quality of the patient with the asymptomatic disease.

The invention discloses an interactive commodity selection method and system based on augmented reality, and relates to the technical field of augmented reality interaction, and the method comprises the steps: obtaining the commodity three-dimensional information of a target commodity and the commodity attribute information corresponding to the commodity three-dimensional information; determining scene reference coordinates of the augmented reality scene and ambient light features matched with the scene reference coordinates according to the spatial perception data of the terminal device, and generating an augmented reality presentation object of the target commodity in the augmented reality scene; obtaining interaction behavior data according to the interaction action of the user in the augmented reality scene; performing association matching on the interaction behavior data and the commodity attribute information to generate a candidate commodity selection feature set; and according to a preset fusion criterion, performing fusion on the candidate product selection feature set to obtain a target product selection decision, and outputting interaction feedback information corresponding to the target product selection decision. According to the application, robust fusion and reliable decision of multi-modal interaction information are realized, and the accuracy and interaction consistency of an augmented reality product selection process are improved.

The invention provides a cross-culture teaching adaptive guiding method and system integrating narrative reasoning and digital interaction, and relates to the technical field of digital interaction. According to the method, the first feature vector is constructed by collecting the culture background and the emotional state of the learner, and the culture portrait label is generated in combination with the multi-dimensional culture evaluation; guiding to generate multi-modal narrative data, executing semantic reasoning and conflict identification, and generating a personalized interaction script; behavior feedback is deployed and monitored in real time in a digital interaction environment, dynamic iteration and closed-loop optimization of teaching content are realized, and culture sensitivity and teaching adaptability are improved.

The invention relates to the technical field of voice interaction, in particular to a method and system for determining a voice reply strategy based on dynamic risk assessment, and the method comprises the steps: obtaining user input and calling a pre-trained large language model to output a risk score in response to a voice interaction request initiated by a user; grading the risk scores based on a preset risk threshold, wherein the risk scores comprise high risks, medium risks and low risks; if the risk is high, immediately entering a strategic refusal response process; if the risk is medium risk, entering a multi-round clarification dialogue process, and continuously recalculating a risk score based on the constructed clarification question and the answer of the user until the risk score is not in a medium risk interval; and if the risk is low, directly entering a normal interaction process. According to the invention, a strategy which can perform fine-grained evaluation and dynamic management and control on a multi-level risk scene and can adaptively switch rejection and clarification in the same closed-loop process can be constructed in a voice dialogue system, so as to give consideration to the interactive experience of safety compliance and natural smoothness.

The invention belongs to the technical field of intelligent interaction, particularly relates to an intelligent interaction method, system and device based on AI communication and a storage medium, and aims to solve the problems that in the prior art, AI scene coverage is narrow and is separated from a business process; the system comprises four modules: a context sensing and modeling module which collects multi-source context information in real time, and generates a three-dimensional context tensor through structured alignment and time sequence normalization; the intention analysis and reasoning module performs intention level decomposition by using a deep semantic model based on the tensor, and outputs an intention recognition result and probability distribution; the response generation and adaptation module is used for generating multi-mode responses such as texts, voices, images or equipment instructions in combination with intention and context tensors, and outputting the multi-mode responses after consistency verification; and the interactive feedback and optimization module collects user explicit and implicit feedback and is used for updating model parameters and strategy weights online to realize continuous optimization of the system.

The invention discloses an intelligent music playing method based on three-dimensional scene interaction, and relates to the technical field of three-dimensional interaction, and the method comprises the steps: extracting a music feature vector of an input audio, inputting a lightweight neural network to output a music genre label, loading a three-dimensional scene in a three-dimensional scene template library based on the music genre label, and generating an initial three-dimensional music space; materializing a control component in the three-dimensional scene into a three-dimensional interactive object, and detecting the position and posture of the hand of the user in the initial three-dimensional music space to perform music playing control; and driving a dynamic element in the three-dimensional scene based on the music feature vector to control the amplitude of a top light beam, the ripple radius and the particle spacing of the central region, and mapping to the initial three-dimensional music space. According to the method, playing, volume and lyric functions are materialized into interactive objects, gesture recognition is introduced, and natural, visual and low-delay three-dimensional interactive experience is achieved; and an intelligent music playing effect with high immersion, high degree of freedom and high consistency is achieved.

The invention discloses a cultural relic exhibition hall AI intelligent shooting system based on binocular vision, and relates to the technical field of cultural relic digitization and interaction, and the system comprises a binocular vision image collection module which is used for shooting and storing a multi-view high-definition image of a cultural relic; the AI image splicing fusion module preprocesses the image and generates a panorama; the cultural relic three-dimensional reconstruction module constructs a three-dimensional model with fine textures; real-time fusion of the intelligent shooting module fusion model and a visitor image is carried out to generate an interactive picture; the interactive output and management module provides related functions and manages data; by integrating binocular vision image acquisition, AI image splicing and fusion, cultural relic three-dimensional reconstruction and real-time fusion intelligent shooting technology modules, intelligent upgrading of cultural relic display and visitor interaction is achieved, the system adopts a binocular camera shooting mechanism triggered by multiple strategies, timing and induction triggering modes are combined, and the intelligent upgrading of cultural relic display and visitor interaction is achieved. The method can flexibly adapt to the demands of different exhibition scenes, guarantees the high efficiency of cultural relic image collection, and avoids the waste of resources.

The invention discloses a voice recognition real-time interaction system and method based on artificial intelligence, and the method comprises the steps: deploying an edge calculation node on a distributed voice collection device, and carrying out the voice feature recognition and voice text conversion of collected conference voice data through the edge calculation node, voice characteristic values and text data of a plurality of nodes are obtained; connecting the plurality of edge computing nodes through a block chain, and transmitting the voice features and text data of the plurality of nodes to a central node; performing style prediction on the voice features and the text data of the plurality of nodes by using the central node to obtain a conference language style; and according to the instruction initiating node, performing interactive answering based on the conference language style. The invention relates to the technical field of voice interaction, and solves the technical problems that an existing voice interaction system is low in long text processing efficiency and insufficient in conference scene dynamic interaction experience feeling.

The embodiment of the invention discloses an expression driving method, device and equipment of a digital human, relates to a data interaction technology, and is used for solving the problem that an expression driving machine of an existing digital human is lack of infectivity. The method comprises the following steps: receiving a voice signal input by a user, and obtaining a voice feature corresponding to the voice signal; processing the voice features based on a preset emotion encoder, and obtaining emotion prediction data corresponding to the voice features; fusing the emotion prediction data with basic features corresponding to a feature map of a preset hybrid encoder through a cross attention mechanism to obtain hybrid features; inputting the mixed features into a preset decoder for decoding to obtain a facial expression coefficient; and performing expression driving of the digital human based on the facial expression coefficient.

The invention relates to the technical field of electric power emergency management, in particular to a multi-scene process emergency system based on an electric power emergency knowledge base and based on natural language processing, a knowledge graph and deep learning and a use method. A traditional electric power emergency plan has the problems of low text structuring degree, insufficient dynamic response capability and the like, so that the emergency plan generation efficiency is low. In the prior art, the fusion capability of multi-source heterogeneous data is lacked, and plan disassembly depends on manual work, so that the requirement of quick response is difficult to meet. In addition, an existing system has obvious defects in the aspects of post responsibility matching, resource dynamic scheduling and the like. Based on the above technical scheme research conclusion, an emergency resource continuous optimization configuration method is analyzed, and a plan digital real-time information interaction technology is combined to realize integrated planning with a new-generation emergency command system to develop a demonstration application scheme.

The invention discloses a task execution method and device for a vehicle-mounted environment, equipment and a storage medium, and relates to the technical field of vehicle-mounted interaction, and the method comprises the steps: obtaining a current task target and current screen state information for controlling a vehicle machine screen; based on a pre-constructed candidate action space, the current task target and the current screen state information, constructing verification prompt information conforming to a preset template; inputting the verification prompt information into a target verification model for action verification to obtain an action verification score; determining a target action from the candidate action space according to the action verification score; and executing the target action to complete the current task target, reducing the delay of the task by changing the large language model from generating a long sequence to outputting an action score, and selecting an optimal action by evaluating all possible actions, thereby reducing illusion and errors when the large language model is directly generated, and improving the success rate of the task.

The invention relates to the technical field of intelligent interaction, in particular to a multi-modal input agent decision interaction method and system. The system comprises a multi-modal input acquisition unit, an input processing unit, a decision strategy generation unit, an interactive execution unit and a data transmission unit. The multi-modal input acquisition unit acquires multi-modal input signal data of a target environment to realize multi-dimensional sensing of the environment; the input processing unit processes the signal data to obtain multi-modal feature data, and the characterization accuracy of the feature data on the environment information is improved by deeply fusing multi-source data to mine internal association; the decision-making strategy generation unit generates a decision-making strategy based on the feature data, and can adjust decision-making logic according to the real-time change of the environment; the interactive execution unit executes interactive actions according to a decision strategy to guarantee accurate conversion of decisions; and the data transmission unit transmits the interaction result data to external equipment to ensure real-time and reliable transmission. The system is suitable for various intelligent interaction scenes.

The invention provides a meta-universe virtual-reality interaction method based on causal invariance, belongs to the field of meta-universe virtual-reality interaction technologies, and is used for solving the problems of poor cross-domain adaptation, insufficient long-tail scene coverage and low dynamic robustness in related technologies. According to the method, through sensing layer causal kernel quality evaluation and data enhancement, reasoning layer causal invariance learning and cross-domain parameter migration, decision layer causal attention intention alignment, execution layer causal reinforcement learning control and iteration layer double-threshold knowledge updating, full-link parameter collaborative circulation is realized in combination with a causal data interface; and finally, the accuracy and the stability of virtual-real interaction of the element universe are improved, and efficient adaptation of cross-domain, long-tail and dynamic scenes is realized.

The invention relates to the technical field of dynamic decision making and real-time interaction, provides a full-motion simulator TCAS simulation method and system based on dynamic decision making and real-time interaction, and solves the problem of low accuracy of flight conflict dynamic prediction and avoidance decision making. The method comprises the following steps: acquiring position coordinates, movement speeds and direction angles of a plurality of flight targets in a three-dimensional airspace; discretizing the three-dimensional airspace into dynamically updated grid units based on the position coordinates, and calculating the risk potential energy value of each grid unit according to the movement speed and the direction angle; in the simulation process, according to the risk potential energy value, dynamically predicting a conflict occurrence probability value in a future set time period through a Monte Carlo algorithm, and generating an avoidance instruction set; after simulation is finished, according to the avoiding instruction set, a conflict report is generated in the real-time interaction display interface, and the conflict report comprises the number of conflicts, the avoiding success rate and the pilot response time. According to the invention, the accuracy of flight conflict dynamic prediction and avoidance decision in a high-density airspace is improved.