19626 results about "Multimedia" patented technology

Disclosed is a chat group management method, including: detecting a message receiving mode corresponding to a chat group; obtaining a degree of interest of a user for chat group messages and an activity degree of the user in the chat group in accordance with a determination that the message receiving mode corresponding to the chat group is a mute-notification receiving mode; determining an importance ranking for the chat group according to the degree of interest and the activity degree; and updating the chat group's position among a plurality of chat groups in accordance with the importance ranking.

The method and systems for automatically identified currently viewing website domain name or a uniform resource locator (URL), receiving, by the server, said automatically identified website domain name or the uniform resource locator (URL), a request or an invitation for initiating a communication including live chat, puts the request for initiating a communication including live chat from the first user and the second user in a communication including live chat queue of the website or the uniform resource locator (URL) associated account, for available or identified or relevant agents to pick up, routing request or invitation for initiating a communication including live chat from the first user and the second user according to a pre-set rules and start a communication including live chat by available agent by selecting particular request for initiating a communication including live chat from the queued communication including live chats.

Techniques are described for identifying functionalities (i.e., user experiences) that are requested by users but are not supported by natural understanding (NU) processing. Some embodiments may involve identifying functionalities by transforming user inputs to functionality-based representations. The functionality-based representations may be grouped into individual functionalities. The user inputs associated with an individual functionality may be evaluated using an NU component to determine whether the functionality is supported. These techniques may enable discovery at a functionality level, rather than at a user input level, an intent level, or an entity level. These techniques may also be used to group user inputs to determine trending functionalities.

Provided herein is a gaming system that presents symbol-bearing reels, a symbol array, and persistent elements external to the array that each have a respective set of visual states and are uniquely associated with a respective state symbol type. The system generates and presents one or more game outcomes, where each game outcome includes spinning and stopping the symbol-bearing reels to land symbols in the array, animating, in response to the landed symbols including a state change event associated with a first persistent element, the first persistent element and associated state symbols to change from a first visual state to a second visual state, and, in response to detecting a symbol trigger event associated with the first persistent element, presenting a game enhancement sequence for a game enhancement that varies based on the current visual state of the first persistent element.

The invention discloses a virtual historical character dialogue method and system with role knowledge and context awareness, and relates to the technical field of man-machine interaction, and the method comprises the steps: constructing a multi-level role depth model; when a question of a current user is received, identifying information of a virtual scene where the current user is located, analyzing micro-expressions of the face of the user and voice rhythm characteristics of speech of the user, analyzing an emotional state and an interaction intention of the user based on a multi-modal fusion algorithm, and generating a user state vector; executing a dynamic Prompt construction program, extracting related information from the multi-level role depth model and the user state vector, and generating a structured Prompt; and inputting the structured Prompt into a large language model, generating a reply text conforming to role features based on questions of the current user, and driving a virtual character model. The method solves the problem that in the prior art, virtual historical figures cannot provide real immersion and credible interactive experience with emotional connection.

Provided is a technique referred to as Voice to Analytics (“Vox2A”), an approach to produce analytic results from a collection of data by using natural language interrogation based on broad but constrained interpretation of user intent to create and present a set of responses containing the sought-after information. The result may be a faster “time-to-analytical answers” tool featuring a shorter user learning curve and easy to navigate experience, making for faster, more informative results, thus improving user productivity.

A method of automatic pre-prompt generation includes receiving at least one user preference from a user device, modifying a system prompt for a machine-learning language model based on the received at least one user preference to generate a modified system prompt, providing the modified system prompt as an initial input to the machine-learning language model, receiving a natural-language text prompt provided by the user to a chat application on the user device, receiving a user identifier from the user device, querying a first database with the user identifier to retrieve first information, generating a representation of the first information and the natural-language prompt, querying a second database using the representation to retrieve second information, and generating a modified text prompt based on the natural-language prompt, the first information, and the second information.

The present invention relates to a system for transforming static websites into artificial intelligence (AI)-enabled interactive multi-modal conversational platforms. The system comprises a computing device having a processor for receiving user queries as text or speech input through an input module cooperating with a speech-to-text module. A natural language processing (NLP) module interprets intent, classifies user context, and retrieves grounded information from multiple webpages. A persona adaptation module dynamically modifies vocabulary, tone, and avatar representation across roles such as sales assistant, recruiter, educator, healthcare professional, etc. A response generator module produces structured natural language output, transmitted to a text-to-speech synthesis module and an avatar generation module to render synchronized lifelike video responses. An output rendering module displays multi-modal responses include text, audio, and video, thereby enabling direct navigation and escalation beyond limitations of conventional static websites.

System, process, and method for gamifying physical assets, digital assets, and virtual assets through advertising and e-commerce, and system and method for personalized digital twin LLM chatbot gamification in e-commerce and emotional intelligence development. The first aspect of the invention is a system and process for creating and training a personalized digital twin LLM chatbot assistant. The digital twin is personalized for a given human user using training data regarding the human user. A second aspect of the invention is a system and process of creating and playing an e-commerce game, including the mechanics of the game. The e-commerce game may be created and / or played by employing personalized digital twin LLM chatbot assistant such as that described in the first aspect of this invention. State of the art technologies such as sensors, IoT devices, wearable devices, and VR / XR / AR can be integrated into the game.

Systems and methods are described for enabling asynchronous experience sharing between users visiting the same environment at two different times. First image data is received, captured during a first time period, wherein the first image data comprises data characterizing the environment in three dimensions. Stored second image data is accessed, the stored second image data captured during a second time period earlier than the first time period, the stored second image data characterizing the environment in three dimensions. A display image is caused to be rendered at a user device during the first time period based on the first image data, the display image comprising an object from the second image data.

Systems, methods, and computer-readable media provide a context-specific prompt to answer a user query. The systems, methods, and computer-readable media determine a context based on content of a natural language request and / or determine a role of a user who submitted the natural language request. Additionally or alternatively, templates or RAG sources that will be used for prompt generation may include financials domain-specific knowledge or other domain-specific knowledge or insights. Inclusion of this additional information in the prompt enhances the context to promote more accurate results from a large language model. In one embodiment, the prompt templates are created from various RAG sources, such as payables, general ledger, receivables, and asset management, containing structured data and information specific to the financial domain, enterprise, or other domain, which helps craft accurate prompts. A prompt is generated that identifies a subset of available fields and other selected information based on the role or other context. The prompt template may contain domain-specific knowledge uses a relevant domain or enterprise information to drive relevant results, and an executable query is generated by a large language model based on the prompt. The executable query causes data to be retrieved from a database to generate a result, and information is displayed based at least in part on the result.

This disclosure relates to techniques for generating and utilizing custom stickers in a digital communication environment. A technique involves receiving a text-based message input during a chat session and using a generative language model (e.g., a Large Language Model, or LLM) to create a text prompt. This prompt is then used by a generative image model to produce a custom sticker. The generated sticker is sent to a client device where it is displayed in a sticker tray alongside other selectable stickers. Users can select and send these stickers directly within their chat interface, enriching communication with visually expressive and contextually relevant imagery.

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.

In some examples, there may be provided systems, devices, and methods for using data from disparate databases to determine characteristics of a set of users within an organizational unit and generate customized user interface elements for display within a user interface.

Various examples, systems, and methods are disclosed relating to an agentic curation pipeline. One system can process questions and other inquiries about video content by using a combination of models and stored information. The system can receive a query related to an event in a video, selects relevant portions of the video using embeddings, and apply the selected video data and a related sub-query to a video model. The output from the video model can be used by a language model, along with stored context, to generate an answer to the original query. The system can returns the answer to the requester.

An apparatus, including a computer including a database which stores a controllable healthcare record and information contained in a master records file, and a distributed ledger and Blockchain technology system. The apparatus facilitates a video call between a user device and a provider device. The computer, after processing information for updating the controllable healthcare record, processes information for identifying a plurality of electronic records for the individual and a second healthcare provider associated with each electronic record. The computer updates each of the plurality of electronic records, and generates a record update message. The computer transmits the record update message to each of a plurality of second provider devices associated with each second healthcare provider. Information regarding the update to the controllable healthcare record and the update to each of the second records is stored in the distributed ledger and Blockchain technology system.

The invention belongs to the technical field of medical treatment and public health, and particularly relates to a hypertension group knowledge recommendation method and system based on a large language model multi-agent. Hypertension knowledge question-answer pair information, medical short video information and user personal health portraits are finely extracted by constructing a hypertension knowledge question-answer pair library; according to the method, video content quality evaluation and matching degree evaluation are performed, and user platform interaction data adjustment is combined, so that personalized and accurate knowledge recommendation services can be provided for hypertension users, the requirements of hypertension patients for health knowledge are met, the accuracy and effectiveness of knowledge recommendation are improved, and self-health management of the patients is facilitated.

In some embodiments, an electronic device presents an M R environment including real content and / or virtual content. In some embodiments, a client application provides an API with a target region of the MR environment, one or more criteria, and a presentation effect. In response to the one or more criteria being satisfied, the electronic device presents the target region of the MR environment with the presentation effect.

The invention relates to the technical field of advertisement effect evaluation, in particular to a cross-screen interactive advertisement effect evaluation system based on multi-modal agent driving, which comprises the steps of collecting advertisement playing data of an advertisement on target equipment, obtaining a login account and a geographic position of the target equipment, performing account verification and distance verification within advertisement putting time, and obtaining the advertisement playing data of the target equipment. Identifying to obtain a cross-screen associated device of the target device; monitoring the running state of the cross-screen associated equipment to obtain user behavior data; constructing a user cross-screen behavior link according to the time sequence of the user behavior data; performing analysis based on the advertisement playing data of the target equipment and the user cross-screen behavior link of the cross-screen associated equipment to obtain cross-screen associated behavior data; and performing user conversion analysis of different advertisement space types based on the cross-screen association behavior data, and calculating an advertisement cross-screen interaction index. According to the method and the device, the advertisement effect is accurately evaluated by identifying the cross-screen behavior of the user.

A method of automatic pre-prompt generation includes receiving, by a user device, an indication of at least one user preference, where the at least one user preference indicative of at least one first characteristic preferred by a user of natural-language outputs generated by a machine-learning language model. The method further includes, by a server, receiving a natural-language text prompt provided by the user, receiving the at least one user preference from the user device, modifying a system prompt based on the received at least one user preference and the at least one first operator preference, providing the modified system prompt as an initial input to the machine-learning language model, providing the natural-language text prompt as an input to the machine-learning language model to generate a natural-language text output after providing the modified system prompt, and transmitting the natural-language text output to the user device.

Dialogue state tracking for voice assistants involves correctly tracking intent and entities of a task that a user is performing. A dialogue state, having a tracked intent and one or more tracked entities, can then be used to perform the task. Building a dialogue state tracking system within a voice assistant is not trivial. In some embodiments, a dialogue state tracking system involving one or more large language models can be implemented downstream of a natural language understanding system to produce the tracked intent and the one or more tracked entities. In some embodiments, a dialogue state tracking system involving one or more large language models can be implemented upstream of a natural language understanding system to produce rephrased natural language text, which is in turn processed by the natural language understanding system to produce the tracked intent and the one or more tracked entities.

The embodiment of the invention provides a mobile banking multi-mode interaction method and system based on a language user interface, and relates to the field of financial science and technology, the method comprises the following steps: obtaining input information of multiple modes input by a user, and fusing the input information of multiple modes to obtain a unified natural language instruction; inputting the unified natural language instruction into a large language model for intention classification and parameter extraction to obtain an operation intention corresponding to the unified natural language instruction and a corresponding service parameter; and executing the operation intention according to the unified natural language instruction and the service parameters. The problem that in the prior art, multi-mode input information in mobile phone banking application is mutually separated, and user intentions cannot be analyzed and understood in a collaborative mode is solved.

Methods and systems enabling multimodal inputs for interacting with a live digital object are provided. The system receives the live digital object which includes a digital artifact extracted from a digital model file through a model representation. The system receives a user's security level and determines the user's access permission and modification permission to access and modify the digital artifact. The system accesses a multimodal interface configured to receive a conversational input and a spatial input, outputs the digital artifact to the multimodal interface based on the access permission, receives from the multimodal interface a conversational input and a spatial input from the user, and generates a modified digital artifact from the digital artifact via the digital model representation, based on the modification permission and on the conversational or spatial input. The multimodal interface may include conventional interfaces (GUIs / APIs), conversational interfaces (text / voice), and spatial computing interfaces (VR / AR / MR / gestural).

Provided herein are techniques to facilitate synchronizing audio streams for a conference call involving multiple microphones utilized at a same location or proximity to one another. In one example, a method may include obtaining, by an aggregating node, each of an audio data stream from each of a plurality of participant devices that are proximate to each other within a conference space for a conference session in which each audio data stream obtained from each participant device comprises audio data and synchronization information, wherein the synchronization information is based on a synchronization sound broadcast during the conference session and received by each of the plurality of participant devices; and synchronizing, by the aggregating node, the audio data of each audio data stream based, at least in part, on the synchronization information included in each audio stream obtained from each of the plurality of participant devices.

Systems, methods, and non-transitory computer readable media including instructions for providing private answers to silent questions are described. Providing private answers to silent questions includes receiving signals indicative of particular facial micromovements in an absence of perceptible vocalization; accessing a data structure correlating facial micromovements with words; using the received signals to perform a lookup in the data structure of particular words associated with the particular facial micromovements; determining a query from the particular words; accessing at least one data structure to perform a look up for an answer to the query; and generating a discreet output that includes the answer to the query.

The invention relates to a man-machine interaction method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: acquiring interaction content input by a user; scene recognition is carried out on the interaction content through a large language model, and a scene label of the interaction is determined; determining a target long-term memory partition corresponding to the scene tag from a plurality of long-term memory partitions preset for the user; inputting target long-term memory content in the target long-term memory subarea and short-term memory content stored in a short-term memory area preset for the user into an intelligent agent; the intelligent agent is used for generating reply content for the interaction content according to the target long-term memory content and the short-term memory content. By adopting the method, effective association and collaborative calling of different scene memories can be realized, and the dynamic requirement of a user on coherent interaction in multi-scene switching is met.

A system to personalize a shopping experience in a conversational commerce platform is disclosed. The system includes a processing subsystem having a user interface module for consumer input and an input conversion module that processes and translates this input using a large language model (LLM) engine. The engine module features a catalog facet creation module that structures product information, a facet enrichment module for detailed descriptions, images and buyers' profile, and a customer profiling module utilizing natural language processing to understand customer needs. An AI merchandising module presents optimal product facets to customers based on profiles and historical data. Additionally, a conversational commerce module facilitates product selection through guided conversations, while a personalization module tailors recommendations. The system also includes a data collection and analytics module for performance tracking and a training and optimization module for continuous improvement of the LLM.

A social media platform provides a map-based graphical user interface (GUI) for accessing social media content submitted for public accessibility via the social media platform supported by the map-based GUI. The GUI includes a map providing interactive location-based searching functionality in that selection of a target location by the user in the GUI, such as by tapping or clicking at the target location, triggers a search for social media content having geo-tag data indicating geographic locations within a geographical search area centered on the target location. A search period for which content is returned is dynamically variable based on the duration for which the tap or click is held.