1121results about How to "Improve interactivity" patented technology

The invention discloses an exhibition hall robot visual language navigation method based on a large model, belongs to the field of exhibition hall robots, and aims at solving the problems existing in an existing exhibition hall robot. According to the method, an exhibition hall robot multi-mode scene sensing system senses a current scene, and candidate target objects are obtained through fusion features of RGB images and laser point clouds; extracting image features of all candidate target objects in the scene; according to the exhibition hall robot multi-mode environment understanding system, an exhibition hall robot receives a voice instruction, a visual language multi-mode large model is used for understanding a target object and a user intention, then high-dimensional semantic features of a target object text are extracted from the system, and the target object is found out from candidate target objects; according to the exhibition hall robot intelligent navigation system based on the multi-modal large model, an exhibition hall robot carries out path planning and autonomous movement according to a pose sequence generated by an intention, and self behaviors are dynamically adjusted according to a real-time changing scene provided by the exhibition hall robot multi-modal scene sensing system.

The invention discloses a medical visual question-answering method and system based on multi-task modeling, and the method comprises the steps: carrying out the feature extraction of a to-be-analyzed medical image through a visual encoder, obtaining an image feature, inputting a preliminary question instruction and historical question-answering data into a dialogue large model to generate a question instruction, and obtaining a text feature through a text encoder; carrying out feature fusion on the obtained text features and image features, and carrying out self-attention image importance weighting processing and image-text alignment to obtain image-text fusion representation; and inputting a multi-target output projection layer, carrying out multi-task prediction, outputting question answers, image categories and important region masks, inputting the question answers and the image categories into a dialogue large model, and finally generating diagnosis opinions with detailed description in combination with dialogue context and multi-round interaction data and in combination with the important region masks. According to the invention, the interaction experience and the performance of the question and answer system are improved, and more accurate medical diagnosis in multi-modal complex information is facilitated.

The invention provides a three-dimensional geological modeling parameter optimization method and system based on deep learning, and relates to the field of geological prospecting and modeling.The method comprises the steps that drilling data and remote sensing data of a geological prospecting area are obtained, and multi-source geological data of three-dimensional geological modeling are formed; generating geological profile map data of the geological features according to the drilling data, generating landform profile map data corresponding to the topographic features according to the remote sensing data, and extracting boundary information of the geological exploration area; carrying out gridding processing on a three-dimensional space, dividing a geologic body of the geological exploration area into a plurality of small grid units, and defining geological modeling parameters; the preliminary three-dimensional geological grid model is constructed according to the geological profile map data, the landform contour map data and the boundary information, the size and the resolution of the grid are dynamically adjusted according to the geological change area, the three-dimensional geological model is obtained through optimization and adjustment, the modeling precision is improved, manual intervention is reduced, and computing resources are saved.

The invention relates to the technical field of disease follow-up visit, in particular to a health state assessment system applied to disease follow-up visit, which comprises a data acquisition module, a data preprocessing module, a health state assessment module, a personalized health management suggestion module, a dynamic health risk prediction module and a visualization module, the data acquisition module acquires multi-dimensional data of a patient and performs data fusion and integration, the health state evaluation module evaluates the health state of the patient based on multi-level feature extraction and a deep learning model, and the personalized health management suggestion module combines a health state evaluation result and historical data to obtain a personalized health management suggestion result. Customized health management suggestions are generated through a rule engine, and the dynamic health risk prediction module predicts future health risks of patients and provides real-time early warning by using a time sequence analysis model. The visualization module displays health assessment and management suggestion results through a chart and an interactive interface, and the accuracy and individuation degree of health management are improved.

The invention belongs to but not limited to the technical field of emotion recognition, and discloses a multi-modal classroom emotion recognition method and system based on modal adaptive learning, and the method comprises the steps: building a multi-modal data collection system, collecting the multi-modal data, such as texts, audios and videos, in a classroom teaching process in real time, and carrying out the real-time collection of the multi-modal data; and preprocessing and feature extraction are carried out on data of different modes. For emotion expression feature differences of different classroom scenes, a multi-modal data fusion method based on adaptive modal scoring (AMS) is provided, and a time sequence modeling and emotion classification model is constructed. The multi-modal fusion and time sequence modeling mechanism simulates the multi-dimensional perception of the teacher on the emotional states of the students in the class, and enhances the interpretability of the emotion recognition system. According to the system, weighted fusion is carried out on data features from texts, audios and videos through fusion of multi-modal data, and complete emotion feature representation is formed.

The invention provides a large language model intelligent interaction method and system with memory management capability in the technical field of artificial intelligence. The method comprises the following steps: S1, creating a work memory module, a long-term memory module, a memory fusion module and an intelligent interaction module; s2, acquiring external knowledge and integrating the external knowledge into a long-term memory module; s3, the intelligent interaction module obtains an intention sequence based on a user query statement and sends the intention sequence to a work memory module; s4, the memory fusion module retrieves context information from the long-term memory module based on the user query statement and sends the context information to the working memory module; s5, the work memory module constructs a work memory sending intelligent interaction module based on the intention sequence, the context information and the system instruction; s6, the intelligent interaction module outputs a query result based on the working memory; s7, a memory fusion module extracts semantic memory and plot memory from user query statements and query results and stores the semantic memory and plot memory in a long-term memory module. The method has the advantage that the man-machine interaction performance is greatly improved.

The invention provides a business process construction method combining a workflow engine and a dynamic form, which relates to the technical field of low-code platforms, and comprises the following steps of: establishing a data table according to a business, selecting and importing the data table in a code generation module, generating a basic code package, re-operating a main program compiling code package and loading the code package to a JVM (Java Virtual Machine) operating environment; creating a dynamic form on the basis of the entity class information of the code package through a visual form designer of the dynamic form module, and outputting dynamic form configuration in a JSON (JavaScript Object Notation) format; according to the method, the dynamic form and the process engine are combined, highly flexible business process design can be realized, a user can dynamically design the form and the process model as required to meet different business requirements, and the user-defined component can be designed according to a business data structure and common functions, so that the form can better adapt to a specific business scene, and the user experience is improved. And the user experience and the working efficiency are improved.

The invention discloses a three-dimensional scene re-coloring optimization method based on Gaussian splashing and deep learning, and the method comprises the following steps: S1, constructing a multi-view data set of a given scene, and generating an initial point cloud; s2, based on the initial point cloud, extracting a representative color set from all input pixels, generating a palette and taking the palette as initial setting; s3, rendering a multi-view result picture by using the palette and a Gaussian splash algorithm, calculating a loss function, and generating an optimized Gaussian radiation field through back propagation optimization parameters; and S4, re-rendering the scene and generating a re-coloring result based on the optimized Gaussian radiation field and the palette color modified by the user. According to the method, the Gaussian splash algorithm and the deep learning technology are combined, efficient re-coloring optimization of the three-dimensional scene is achieved, and the method has the advantages of being visual in editing, accurate in illumination expression and real in rendering.

The invention discloses an AI digital human interaction system based on emotion recognition, relates to the technical field of emotion calculation, and improves the accuracy of emotion recognition through multi-modal emotion data acquisition and processing of an emotion primary recognition module and a secondary recognition module. The system effectively distinguishes complex emotions, such as fatigue and depression, of the trainee in the virtual education task by calculating the first emotion coefficient and the second emotion coefficient; secondary emotion recognition is carried out, so that misjudgment is reduced, and the emotion state recognition accuracy is ensured; through an emotion feedback module, the system dynamically adjusts the expression, intonation and interaction frequency of the AI digital human according to a second emotion coefficient, so that the emotion feedback is more natural, and the emotion recognition sense of the student is enhanced; besides, the culture adaptation analysis module collects cross-culture emotion data based on the culture background of the trainee, calculates and evaluates a culture adaptation coefficient, and automatically adjusts an emotion recognition and feedback strategy, thereby improving the adaptability of the system in a multi-culture environment and the accuracy of emotion expression.

According to the intelligent home environment intelligent regulation and control system and the control method thereof, various intelligent sensors are arranged, various environment data such as indoor temperature, humidity and illumination are monitored in real time, the data are preprocessed and then sent to a data analysis layer, data features are extracted according to the monitored data and historical data based on the deep learning technology, and user preferences are deduced; the control parameters are adjusted and sent to the equipment control layer, a specific instruction is sent to an indoor smart home, an air conditioner, a humidifier or a curtain and the like are controlled to accurately control the indoor environment, the living preference of a user is met, and in the process, the effect monitoring and dynamic adjusting layer monitors the adjusting condition in real time, and the user experience is improved. If the ideal effect is not achieved after adjustment, the equipment control layer is controlled to continue adjustment, in the process, the abnormal condition of the system is detected, the power consumption of the equipment and other data are monitored at the same time, normal work of the system is guaranteed, possible faults are predicted, a user is reminded in time, and safe and energy-saving operation of the whole system is guaranteed.

The invention discloses a method and device for automatically converting a cross-format document into a Markdown document and a form enhancement method and system. The Markdown document conversion method comprises the following steps: firstly, obtaining a document image; mining hidden structure information from the document image, wherein the hidden structure information comprises target elements and hierarchical relationships among the target elements; performing semantic content analysis on the document image based on the structure information to obtain a semantic content analysis result; extracting key information in the document image according to an analysis result; the key information is converted into a Markdown format, preliminary formatting is carried out in a form or list mode, and a preliminary Markdown form is obtained; and finally, optimizing the preliminary Markdown form to form a target Markdown form, so that the cross-format document is automatically converted into the Markdown. According to the method, a complex nested structure and a form with irregular layout in the document can be effectively identified and converted, and the integrity and readability of form information when the form is converted into the Markdown format are ensured.

A video perspective method based on virtual reality relates to the technical field of virtual reality, and comprises: at least two cameras for capturing video information in real time, the cameras being provided with spatial positions and angles; performing geometric correction on the video information; the eye movement tracking module monitors the gazing direction of the eyes of the user in real time and adjusts the display position; the eye movement tracking module tracks eyeball movement; reconstructing a three-dimensional model of the surrounding environment of the user; based on the three-dimensional model, determining a relative position relationship between the virtual object and the real object; the head posture sensor obtains head movement information of a user; performing semantic segmentation on the video frame through a deep learning algorithm; and synthesizing the video information and the virtual content on the head-mounted display device, and outputting the synthesized video information and virtual content. The technical problems of visual discomfort and dizziness caused by position mismatching can be solved, and natural fusion of a real scene and a virtual scene is realized.

The invention relates to the technical field of real-time image superposition, in particular to a bridge inspection method and system based on AR, and the method comprises the following steps: shooting a bridge on site, capturing a real-time image of a structure, and recording vibration frequency, displacement change and stress data by using acceleration, displacement and strain sensors; and synchronously integrating the structure real-time image, the vibration frequency, the displacement change and the stress data, and naming the data as multi-dimensional dynamic monitoring data. According to the method, the vibration frequency, the displacement change and the stress data are integrated in real time, so that the real-time performance and the analysis depth of the multi-dimensional dynamic monitoring data are remarkably improved, the high fusion of a real-time image and a three-dimensional model is realized, the accuracy of data visualization is enhanced, an abnormal region is directly visible through the change of colors and textures, and the accuracy of data visualization is improved. According to the method, the structure safety monitoring intuitiveness and interactivity are improved, in addition, through time sequence analysis, structure changes under different environment conditions are accurately simulated, and prospective risk prediction is provided.

The invention relates to the technical field of environment monitoring, in particular to a natural reserve ecological monitoring result display system based on geographic information data, which comprises a data acquisition module, a data fusion module, a dynamic GIS module, an intelligent analysis module, a multi-dimensional display module, an interactive report generation module and a user interaction module. Wherein the data acquisition module is used for acquiring ecological monitoring data; the data fusion module is used for carrying out fusion processing on the multi-source ecological monitoring data; the dynamic GIS module is used for mapping the fused ecological monitoring data into a geographic space in real time; the intelligent analysis module is used for intelligently analyzing the geographic space data; and the multi-dimensional display module is used for displaying the ecological monitoring result. According to the system and the method, the ecological data processing capability is improved through an efficient data fusion technology and an advanced intelligent analysis module, and meanwhile, the user experience is greatly enhanced through an interactive report generation and multi-dimensional display module.

The invention discloses a tuning method and device for vehicle-mounted music, a medium and a product, and relates to the technical field of music playing, and the method comprises the steps: obtaining the driving parameters of a vehicle in a process that a playing device of the vehicle plays target music; determining a track control parameter corresponding to each audio track based on the driving parameter of the vehicle; adjusting audio data of each audio track of the target music based on the track control parameters to obtain adjusted audio data corresponding to each audio track; and generating tuned target music based on the adjusted audio data corresponding to each audio track, and playing the tuned target music. The track control parameters of the audio tracks are determined according to the driving parameters of the vehicle so as to control the audio tracks of the music, so that the music can be dynamically adjusted according to the driving process of the vehicle, the interactivity between the music and the driving process is enhanced, and the driving experience of a driver is improved.

The invention discloses a personalized rehabilitation plan generation method and system based on multi-modal data, and relates to the technical field of medical rehabilitation, and the method comprises the steps: obtaining physiological data, motion data and emotion and cognition data of a patient; preprocessing the physiological data, the motion data and the emotion and cognition data to obtain multi-modal fusion data; analyzing the multi-modal fusion data by adopting a pre-trained machine learning model, and determining the rehabilitation potential and demand of the patient to obtain an evaluation result; a personalized rehabilitation plan of a rehabilitation training type is automatically generated according to an evaluation result, and training parameters, psychological counseling and nutrition suggestions are generated according to the conditions of the patient. According to the personalized rehabilitation plan generation method and system based on the multi-modal data, accurate evaluation can be carried out according to the conditions of the patient, the personalized rehabilitation plan is generated, the rehabilitation efficiency of the patient can be improved, and it is ensured that the rehabilitation process is more scientific and efficient.

The invention discloses a light-weight government affair questionnaire intelligent touch and analysis system and method based on a fusion message, and the system comprises an integrated message application platform operation interface which is used for the submission, application, strategy definition and transmission of a customer message; the questionnaire engine is used for generating questionnaires, issuing strategies and performing multi-dimensional statistical analysis on questionnaire results; the intelligent message scheduling engine is used for realizing AI generation of rich media messages, multi-channel intelligent reach distribution, optimal reach mode selection and summary analysis of reach mode results; and the electronic fence data engine is used for processing operator real-time signaling big data and capturing operator numbers and accurate touch short messages in a specified range. An efficient and convenient short message creation and auditing mechanism, flexible and diversified questionnaire construction, intelligent rich media message generation, accurate regional orientation and audience access, intelligent distribution, high interactivity, comprehensive and deep data analysis and report generation can be realized.

The invention provides a tourism information release management method and system based on artificial intelligence and big data. The method comprises the following steps: collecting user emotional states monitored in real time and classifying the user emotional states; recommending suitable tourism activities to the user according to the emotional state of the user; an AR scene is generated according to the personalized activity recommendation list, a user interacts by selecting the AR scene, and the AR scene is adjusted and optimized in real time according to real-time interaction; according to feedback data collected in real time in an AR scene, optimizing recommendation planning and experience contents; the recommendation strategy is dynamically adjusted in combination with historical preference data of the user, emotion feedback of the user and particularity of the tourism scene; and multi-level data integration, real-time resource optimization and dynamic scheduling are realized. According to the invention, real-time feedback and dynamic adjustment of tourism management are realized, so that the user satisfaction is greatly improved, and the requirements of modern tourists on individuation, interactivity and instantaneity are met.

The invention provides a remote acquisition system for operation data of gas equipment, and relates to the technical field of data processing, and the remote acquisition system comprises the steps: capturing the time-varying rule of the state of the gas equipment through learning the long-term dependency relationship in a sequence, and generating key features containing time sequence information; fusing the time sequence characteristic representation output by the long short-term memory network with the equipment attributes and relationships in the knowledge graph to form a characteristic vector reflecting the comprehensive state of the gas equipment; comprehensively analyzing the feature vector to obtain a hidden mode related to the risk of the gas equipment; and based on the hidden mode related to the gas equipment risk, adopting a multi-classification support vector machine to predict the risk level so as to obtain a final risk level prediction result. According to the invention, risk assessment of the operation state of the gas equipment can be realized, so that the safety and the operation efficiency of the equipment are improved.

The invention discloses a mobile game scene interaction intelligent optimization method based on a generative adversarial network, and aims to improve the game experience of players. Comprising the following steps: S1, collecting behavior data and interaction information of a player in a mobile game, and generating a preliminary behavior feature model; s2, constructing a generative adversarial network model; s3, generating diversified game scene interaction examples according to the trained generator; s4, evaluating and optimizing the generated scene interaction example by using a discriminator; s5, real-time feedback of the player is received, and the behavior feature model of the player is updated; s6, dynamically adjusting a generation strategy based on the updated behavior feature model, and optimizing a scene interaction effect; s7, environment data are integrated, scene interaction is optimized in real time, and the immersion of players is enhanced; and S8, providing user-defined scene interaction options for the players, and allowing the players to adjust according to personal preferences. The interactive experience and game fun of players can be effectively improved.

The invention relates to the technical field of tourist route recommendation, in particular to a tourist route recommendation system and method based on big data. The method comprises the following steps: collecting travel demand data and basic sign information of a user, and performing hierarchical analysis on a demand to obtain master / slave demand data; then, through demand behavior intersection analysis, muscle soreness intensity is simulated in combination with user physical sign data, and the physical degeneration rate is further estimated; based on the physical decline rate, making a rest strategy, and optimizing distribution and adjustment of tourist routes; and finally, transmitting the adjusted tourist route data to a user terminal. According to the invention, the tourist route recommendation technology is improved, so that the tourist route recommendation technology is more perfect.

The invention discloses a real-time cultural tourism path optimization and adjustment system based on big data analysis, and relates to the technical field of cultural tourism path optimizing.The system comprises an acquisition and analysis module, the acquisition and analysis module is connected with a combination and matching module, the combination and matching module is connected with a path optimization module, and the path optimization module is connected with a data processing module. The path optimization module is connected with an interaction feedback module, and the collection and analysis module is used for collecting tourism behavior characteristic information of tourists in real time by using a big data analysis technology. According to the real-time cultural tourism path optimization and adjustment system based on big data analysis, a personalized model is established, tourism paths can be customized for tourists, unique tourism requirements and preferences of the tourists are met, the satisfaction degree and participation degree of the tourists in the tourism process are improved, the tourism paths can be adjusted in time according to real-time external data, and the tourism efficiency is improved. The tourists are prevented from being caught in unfavorable conditions such as congestion and severe weather, and smooth and efficient travel itinerary is ensured.

The invention provides a voice education robot based on children voice modal characteristic perception, and relates to the field of intelligent education, the voice education robot adopts an AI and end-to-end voice analysis and processing technology to extract a time sequence of pitch and sound intensity from a voice input signal, and performs time sequence association mode analysis on the time sequence; the method comprises the following steps: performing feature generality compensation on pitch time sequence correlation mode features and sound intensity time sequence correlation mode features, and meanwhile, performing fragment embedding coding on voice input signals so as to intelligently generate education reply voice through compensated features and semantic embedding features of each voice input signal fragment. Therefore, the robot can dynamically adjust the reply content and generate personalized education reply voice according to the real-time feedback and emotion change of the child, which is helpful for enhancing the interaction effect and improving the learning enthusiasm of the child.

The invention relates to a multi-agent oral hospital diagnosis and treatment model establishment method and device, and the method comprises the steps: carrying out the fine adjustment of an existing large-scale language model through employing an efficient method, and enabling the model to better meet the specific demands of the medical field. And on the basis of fine tuning, a feedback mechanism based on artificial intelligence is further utilized, and the expression of the model is optimized through reinforcement learning, so that the system is more intelligent and high in adaptability when simulating doctor-patient interaction. Through the multi-agent framework, a complex medical interaction process among a patient, an examiner, a medical student and a main doctor can be simulated, so that a training platform close to a real clinical environment is provided. Wide experimental results and comprehensive evaluation prove that the multi-agent oral hospital technology based on role playing can well improve interactivity and practicability of medical education, and meanwhile it is ensured that medical students can learn and practice clinical thinking and decision skills in a safe environment. The invention also relates to a device and a memory.

The invention provides a customer service interaction method, an interaction device, equipment, a storage medium and a program product, and relates to the technical field of computers. The customer service interaction method based on the large language model comprises the following steps: performing intention scene recognition on a received user question; identifying that the user question belongs to a specified intention scene, and determining a corresponding domain knowledge base matched with the user question; performing enhanced retrieval on the knowledge base in the corresponding field based on the user question to obtain a business knowledge fragment for enhancing the user question; and inputting the business knowledge fragments into a large language model, so that the large language model performs filtering type question reply processing based on the business knowledge fragments, and outputs reply information of the user question based on a processing result. According to the technical scheme, the real intention of the user in continuous interaction can be deeply analyzed, the content which the user wants to consult can be more accurately grasped, and the consulting requirement of the user is better met.

The invention relates to the technical field of multimedia regulation and control, in particular to a regulation and control system for a digital multimedia exhibition hall, which comprises a multimedia content control module for managing a digital screen, a projector and audio multimedia in the exhibition hall in real time and realizing dynamic switching of display contents and multimedia linkage; the environment regulation and control module is responsible for controlling light, sound, temperature and humidity in the exhibition hall, synchronously adjusting the exhibition hall environment and exhibition content, monitoring environment parameters in real time by using an intelligent sensor, providing an intelligent adjustment scheme, and monitoring behaviors of visitors in real time by using a sensor, a camera and intelligent bracelet equipment. The digital multimedia exhibition hall regulation and control system integrates an intelligent control technology, audience behavior monitoring and data analysis, and has the functions of real-time regulation and control, dynamic interaction, data feedback and optimization and the like. Through the unified central control system, the exhibition hall can intelligently adjust the multimedia content and environment according to the actual exhibition content and the behaviors of visitors, and the efficient and flexible exhibition effect is achieved.

The invention discloses a configurable flexible job shop scheduling method based on a multi-agent game model, and the method comprises the steps: mapping a scheduling problem into a dynamic disjunction graph model to describe the relation between a process and equipment, representing process nodes, equipment nodes and the mutual relation through a node set and an edge set, and combining the flexibility of a dynamic disjunction graph to obtain a flexible job shop scheduling model. And matching of equipment and processes is dynamically adjusted according to changes of production requirements, so that the equipment utilization rate is optimized. And a clustering method based on structure entropy is adopted, and process nodes are clustered into sub-graphs, so that the search space of a scheduling problem is reduced, and the calculation complexity is reduced. Construction of an order agent and an equipment agent and a game and cooperation process between the order agent and the equipment agent are covered. And each agent optimizes a decision through a deep Q network, and cooperates or competes according to a respective target. An automatic optimization configurator is used for optimizing hyper-parameters and a network structure of a deep Q network in a multi-agent system, and scheduling performance and adaptability are further improved.

The invention relates to the technical field of data processing and three-dimensional model construction, in particular to an intelligent three-dimensional model design method and system based on small-opening press-blow molding equipment. The method comprises the following steps that an intelligent sensor is used for collecting parameters of small-opening press-blow forming equipment, and initial equipment parameter information is recorded; according to the initial equipment parameter information, establishing an equipment three-dimensional initial model by using computer aided design software; and acquiring characteristic data of the glass material drops, inputting the characteristic data of the glass material drops into the three-dimensional initial model of the equipment, simulating a press-blow molding process by utilizing simulation software, and carrying out influence evaluation on the simulated press-blow molding process to obtain a molding process evaluation result. Through a data processing technology, a three-dimensional modeling technology and an automatic control technology, various parameters of the small-opening press-blow molding equipment are associated and evaluated, and an intelligent three-dimensional model of the equipment is constructed; and the accuracy of control operation of the forming equipment is improved, so that the produced glass containers are kept consistent in specification.

The invention provides an interaction method and device, electronic equipment, a storage medium and a program product, and the method comprises the steps: carrying out the semantic analysis of a to-be-processed problem, and generating a reply text and a target action of the to-be-processed problem; determining a first text matched with the target action from the reply text according to the reply text and the target action; performing time alignment on the execution starting time of the target action and the playing starting time of the first text; the reply text is played, and in the playing process of the reply text, according to the execution starting time of the target action and the playing starting time of the first text after time alignment, the target action is synchronously executed when the first text is played, so that synchronization of the action and the reply text can be realized; and the interaction performance is improved.

The invention discloses a meta universe-based conference interaction method, and relates to the technical field of virtual conferences, and the method comprises the steps: extracting the facial features of participants, comparing the facial features with a pre-established facial feature library, obtaining the unique identity of each participant, and recognizing the identities of the participants; after the identities of the participants are determined, position changes of key body joint points of the participants are detected in real time, and specific actions of the participants are judged by analyzing relative positions and movement tracks between the joint points; the method comprises the following steps: receiving the acoustic characteristics of the participant language, converting the voice signal of the participant into a text, and analyzing the semantics and emotion of the text in combination with natural language processing to obtain the language expression intention of the participant. According to the method and the device, the optimal interaction mode can be dynamically selected from the preset library according to different interaction intentions, and the audio and video parameters and the interface layout are adjusted in real time, so that intelligent interaction in a multi-user scene is realized, the interaction experience of a conference is optimized, and the interaction effect can also be improved.