4738 results about "Media content" patented technology

In some embodiments, a computer system displays a caption for a media item at different depths depending on the depth of the portion of the media item over which the caption is displayed. In some embodiments, a computer system displays a user interface element that includes information associated with the media item at different locations relative to the media item depending on attention of the user. In some embodiments, a computer system displays a user interface element that includes information associated with the media item with different visual appearances depending on visual characteristics of the portion of the media item over which the user interface element is displayed.

In some embodiments, an electronic device generates virtual lighting effects while presenting a content item. In some embodiments, an electronic device enhances navigation to a respective playback position of a content item. In some embodiments, an electronic device displays media content in a three-dimensional environment. In some embodiments, an electronic device presents media content in different modes of presentation.

The invention discloses a media content production and distribution integrated system based on multi-agent collaboration, and relates to the technical field of media content production and distribution. The system comprises a content creation multi-task intelligent system, an audience analysis multi-task intelligent system and a media content distribution module, and the content creation multi-task intelligent system comprises a topic selection planning agent, a text creation agent, an article illustration agent and a content evaluation agent. The audience analysis multi-task intelligent system comprises a data processing agent, a user portrait agent and an interest prediction agent, and through functions and cooperation of the agents, an AI large language model and a multi-agent cooperation technology can be introduced, so that a full-service process from media content production to media content distribution can be automatically opened, and the efficiency is improved. And automatic production and personalized distribution of the media content are realized, the production efficiency and the propagation effect of the media content are greatly improved, and practical application and popularization are facilitated.

Systems and methods for semantic temporal segmentation based on topic recognition are disclosed. Text classification and segmentation may be used to index media content for subsequent searches. The method may include using a text classification model to semantically analyze sentences in a text file (such as a transcript) to determine topics with which sentences are associated. The output of the text classification model may be provided to a text segmentation model to enable more-accurate identification of text segments (e.g., paragraphs) within the text file. In some examples, the output of a text segmentation model is provided to a text classification model to enable the text classification model to perform more-accurate classification based on text segments rather than (or in addition to) performing classification on single sentences. The classification of the text segments may be used to assign labels to the text segments to enable subsequent searches based on the labels.

This invention introduces an adaptive system for multi-modal media processing and delivery, addressing challenges in modern digital content distribution. The technology dynamically analyzes and processes media content in real-time, optimizing delivery across diverse devices, networks, and content types. Key features include adaptive processing that adjusts compression, encoding, and delivery protocols based on content characteristics and delivery constraints. The system incorporates artificial intelligence for continuous improvement, learning from historical data and user feedback. It addresses network variability and device diversity, adapting to changing conditions and optimizing content for different platforms. Security and personalization features enable protected content distribution and tailored user experiences. The invention's cross-media optimization approach allows efficient handling of various media formats within a unified framework. Its scalable, modular design suits applications from consumer streaming to enterprise-level distribution. This comprehensive solution aims to enhance content distribution efficiency and user experience in the complex, evolving digital media landscape.

The invention discloses an enterprise-level knowledge management system based on a large language model. The enterprise-level knowledge management system comprises a knowledge storage module, a knowledge analysis module and a knowledge application module, the knowledge storage module is responsible for managing and storing knowledge from different sources, supporting uploading, updating, deleting and sharing of electronic documents and multimedia documents, and is provided with authority control; the knowledge analysis module is used for carrying out deep understanding and structured processing on text and multimedia contents through a special analyzer by utilizing an advanced large language model technology; the knowledge application module provides intelligent retrieval and intelligent question and answer functions and supports advanced applications such as behavior portrait analysis and standard process supervision. According to the method and the system, the acquisition, understanding and application efficiency of enterprise knowledge is remarkably improved by fusing a large language model technology and a traditional knowledge management method, an intelligent, automatic and safe knowledge management solution is provided for an enterprise, and value mining and innovative application of enterprise knowledge assets are effectively promoted.

Methods and apparatus are described for evaluating dubbing of media content. Emotions are identified based on combinations of attributes determined for segments of a source language audio and a dubbed audio. The emotions may be compared to determine emotional prosody transfer between the source audio and dubbed audio. Based on the comparison, a notification is generated indicating whether an emotion classification associated with the source audio matches an emotion classification associated with the dubbed audio.

The invention discloses a convergent media content intelligent label generation and target classification method, and belongs to the technical field of artificial intelligence and convergent media. In order to solve the problems of low labor efficiency, poor rule label flexibility and the like of traditional fusion media content label generation, the deep learning and multi-modal fusion technology is innovatively adopted. In a data processing layer, through deep integration of NLP and CV technologies, feature extraction of multi-source data such as texts, pictures, videos, audios and the like is realized. In a label generation layer, an intelligent label engine is constructed based on a CNN and RNN hybrid model, and a dynamic label library is established in cooperation with a rule matching strategy. And in the classification optimization level, the K-means clustering and hierarchical classification methods are combined to realize adaptive classification and optimization of the labels. Through continuous data training and a user feedback mechanism, the label generation accuracy, the classification efficiency and the system adaptability are remarkably improved, and an innovative solution is provided for intelligent management of the convergence media content.

Implementations relate to generating multi-modal response(s) through utilization of large language model(s) (LLM(s)) and other generative model(s). Processor(s) of a system can: receive natural language (NL) based input, generate a multi-modal response that is responsive to the NL based output, and cause the multi-modal response to be rendered. In some implementations, and in generating the multi-modal response, the processor(s) can process, using a LLM, LLM input to generate LLM output, and determine, based on the LLM output, textual content and generative multimedia content for inclusion in the multi-modal response. In some implementations, the generative multimedia content can be generated by another generative model (e.g., an image generator, a video generator, an audio generator, etc.) based on generative multimedia content prompt(s) included in the LLM output and that is indicative of the generative multimedia content. In various implementations, the generative multimedia content can be interleaved between segments of the textual content.

Methods and systems are disclosed for analyzing media content in response to a trigger, identifying relevant objects displayed within the media content, and generating linkable interactive user elements related to the relevant object that are presented as part of an overlay image for display on a user device. An image and a media content item are accessed and analyzed, interactive user elements are generated and used in an overlay image allowing selection of interactive user elements as a hyperlink to relevant content.

The invention relates to the technical field of audio and video control, and discloses an audio and video player control method based on a voice instruction. The method comprises the steps that an original voice instruction stream of a user is collected, the instruction stream comprises a time domain audio signal sequence, an environment noise spectrum and user pronunciation characteristic parameters, and voice information can be comprehensively captured; multi-modal instruction analysis processing is carried out on the original voice instruction stream, a structured control instruction set containing acoustic control intention identification, semantic operation object description and context correlation parameters is generated, and the analysis precision is improved; then executing player state adaptation based on the set, generating a dynamic control response sequence containing an equipment state adjustment command, a media content positioning parameter and an interface interaction logic identifier, driving a player to execute a multi-dimensional control operation and generating real-time play control effect feedback data; and finally, multi-modal analysis parameters are optimized according to feedback data, a self-adaptive instruction analysis strategy is generated, and the control experience of a user on the audio and video player is optimized.

Aspects of the disclosed technology provide solutions for processing media content to generate customized media content of a target duration. An example method can include receiving media content of a first duration. The media content may include a plurality of video frames. The method can include steps for receiving one or more parameters, which may include a target duration, classifying each of the plurality of video frames of the media content based on a relevance level of each frame, and generating a target media content of the target duration based on the classification of the plurality of video frames of the media content of the first duration. Systems and machine-readable media are also provided.

A presentation assistance system receives information about a presentation to be given and automatically provides feedback to improve the presentation either offline or in real time as the presentation unfolds using computer models, where a presentation is a collection of multi-media content, including but not limited to text, slides and graphics, and audio and video streams. The computer models may be trained based on prior presentations and performance metrics of relevant entities. In particular, the presentation includes interactions with audience members and computer models are used to generate likely participants and related interactions, such as questions or recommendations for improved interactions, relevant to the current presentation based on a set of machine learning and AI models, and, in particular, language models. The language model may be prompted with prior relevant questions to determine questions for the current presentation and evaluate the likelihood that the current presentation effectively answers them.

Systems and methods for reducing the search space by processing media content to refine search parameters. A computing device may obtain the media content in response to receiving a request for inclusion of the media content in a media content knowledge repository, extract an audio component, a video component, and a text component of the media content, and determine attributes within the extracted components. The computing device may determine segment attributes based on a result of correlating the determined audio, video, and text attributes, integrate the segment attributes into the media content knowledge repository, and / or perform any of a variety of responsive actions.

Implementations relate to providing a user feedback mechanism that enables a user to provide feedback towards one or more specific portions of a response. The response can be generated based on processing of a user query using a generative model such as a large language model (LLM). The one or more specific portions can be a textual portion that includes textual content, and / or a media content portion that include media content such as one or more images, one or more videos, one or more audio pieces, etc. The feedback towards one or more of the specific portions of the response can be utilized in training or fine-tuning the generative model (or an additional generative model) via approaches such as supervised training or reinforced learning.

Systems and methods for a media content user interface. A media content provider includes storage for storing and serving video content to subscribers. The media content provider records and or otherwise stores video content from around the world. Subscribers are provided a user interface to the system that includes a side bar. The side bar includes multiple elements representing different categories of video content. By selecting a given category, available content is filtered according to the selected category and presented. Content which is presented may include live broadcast video for multiple channels on multiple television networks or other content providers. The side bar may further include a collection category specific to a given viewer. Selection of such a category may display video content within the collection. Subcategories in the side bar may be selected for further filtering of available content.

The embodiment of the invention provides a media content generation method and device, a storage medium and a program product, and the method comprises the steps: displaying dialogue content in a dialogue window of a first interface, generating target media content according to the dialogue content, and presenting a trigger control of the target media content in the dialogue window, wherein the trigger control is at least used for triggering presentation of the target media content. According to the media content generation method provided by the embodiment of the invention, the information interaction between the user and the system is realized by adopting the dialogue mode, and then the target media content conforming to the creation intention of the user is generated based on the obtained dialogue content, so that the learning cost of the user is reduced, the operation is simple, and the intelligent level of media content generation is improved.

Examples are provided relating to media content editing architectures utilizing machine learning techniques. One aspect includes a method for media content editing, the method comprising: receiving a media content from a user; receiving an editing request for the media content from the user; and editing the media content based on the editing request to generate edited media content by: retrieving a prompt from a prompt pool, wherein the retrieved prompt is selected based on the editing request; parsing the retrieved prompt and the editing request using a large language model to generate one or more editing actions to be performed on the media content; and performing the one or more editing actions on the media content to generate the edited media content.

Distributed media content history and preferences can be stored and maintained by media playback systems including one or more blockchain-capable playback devices. Content record sets, such as content experience record sets and content network record sets, can be stored via distributed ledgers and updated at least in part based on media consumption events performed or detected by playback devices, service providers, or other participants. Such distributed data can also be accessed to facilitate playback of media content for particular users, devices, households, or environments.

Approaches, techniques, and mechanisms are disclosed for media rendering in vehicles. Specific user input is received through an in-vehicle user interface device while the in-vehicle user interface device is concurrently displaying a navigation map. The specific user input is used to generate an audio story selection list for audio stories relating to geographic locations on the navigation map. Second specific user input is received to indicate a specific audio story selection for a specific audio story relating to a specific geographic locations among on the navigation map. The specific audio story is caused to be streamed from a specific media content source and rendered through an in-vehicle audio system built in with the vehicle.

An artificial intelligence-driven sentiment analysis system for social media monitoring, comprising: a data collection module configured to retrieve user-generated content from at least one social media platform via application programming interfaces (APIs); a preprocessing module configured to process and clean the collected data by removing irrelevant content, tokenizing the text, removing stop words, and assigning sentiment indicators to emojis, slang, and abbreviations; a sentiment analysis engine comprising one or more deep learning models, wherein the deep learning models include recurrent neural networks (RNNs), long-short-term memory networks (LSTM), and transformer-based models configured to analyze the preprocessed data and classify the content into one or more sentiment categories; an emotion recognition module configured to detect emotional tones within the content and classify them into predefined emotional categories; a real-time data processing unit configured to continuously monitor social media content and provide real-time insights into moods and emotions; a feedback loop module configured to update and refine the deep learning models through reinforcement learning based on new data inputs and sentiment classification results; and a user interface module configured to visualize sentiment and emotion analysis results in real time, including heatmaps, sentiment trend analysis, and emotional breakdowns.

The invention relates to the technical field of intelligent data processing, in particular to a model training and content auditing management system based on intelligent data acquisition, which comprises an acquisition processing unit, a model training unit and a content auditing unit. The model training unit constructs a multi-modal fusion model, a joint training mechanism of the model learns modal association, adaptive learning rate strategy optimization training and early stop technology anti-overfitting, the trained model is used for content auditing, the content auditing unit receives multimedia content, extracts key frames, audio voice content and subtitle text, and performs feature representation and fusion to obtain a subtitle text. Whether violation occurs or not is judged through the trained model, all the units cooperate with one another, the collecting and processing unit provides a data basis for model training, the model training unit provides a precise model for content auditing, effective auditing of multimedia content is jointly achieved, and legitimacy and health of the content are guaranteed.

Systems and methods for a media content system. A media content provider includes storage for storing and serving video content to subscribers. The media content provider records and or otherwise stores video content from around the world. The system includes display devices configured to identify and tailor content to multiple individual users. Each user may have individual settings which provide for a customized viewing environment and experience. The system is configured to identify users of the system in order to tailor the content as appropriate. In addition, identification of users allows for the identification of the subscription content that corresponds to the user. Based upon identification of a user and corresponding subscription, the user's subscription content may be streamed to any location. In this manner, the users subscribed content may follow the user from home to a friend's house, or elsewhere.

Systems and methods for a media content system. A media content provider includes storage for storing and serving video content to subscribers. The media content provider records and or otherwise stores video content from around the world. Subscribers are provided a user interface that provides context sensitive hints to assist the viewer. The system further enables viewers skip, view, and interact with advertisements.

Systems and methods are presented herein for requesting a version of media content from a server that includes haptic feedback rending criteria compatible with the haptics capabilities of a client device. At a server, a request is received for a media asset for interaction on a haptic enabled client device, wherein the media asset comprises haptic feedback rendering criteria. Based on the request, haptic feedback capabilities of the haptic enabled client device associated with the request is determined. The haptic feedback capabilities of the haptic enabled client device are compared to the haptic feedback rendering criteria of one or more versions of the media asset available via the server. In response to the comparing, a version of the media asset comprising haptic feedback rendering criteria compatible with the haptic feedback capabilities of the haptic enabled client device is transmitted from the server to the haptic enabled client device.

The present invention relates to a lifelogging software application that creates a platform for users to create media content associated with and representative of stories, people, place, events, and other significant moments of an individual's life. The platform creates an environment for individual users to interact with each of and the media content posted thereto. The platform includes a beneficiary and inheritance mechanism that transfers control of media content from one individual to another. The present invention is operable to create a multitude of interactive visual representations of media content, such that the chronological order and location of events are portrayed.

The invention relates to the technical field of data recommendation, in particular to an AI-based multi-platform media content optimization recommendation method and system. The method comprises the following steps: acquiring user equipment parameters and user platform behavior data; user preferences are confirmed based on the user platform behavior data, and user platform preference data are obtained; analyzing the hardware performance of the equipment used by the user according to the parameters of the user equipment, grading, and generating an equipment suitability matrix according to a grading result; performing user active period extraction on the user platform preference data to obtain user active period feature data; performing content loading time consumption analysis on the equipment suitability matrix to generate equipment time consumption data; and extracting format adaptation parameters of the to-be-recommended content based on a preset cross-platform content feature library. According to the method, the compatibility and the response speed of cross-platform media content recommendation are improved by comprehensively considering the user preference, the equipment performance, the time period activeness, the content adaptability and the network fluctuation.

Described herein is a technique for processing a received media content item (e.g., a message), received at a messaging application of a first end-user of a messaging service, to generate a selection of some predetermined number of recommended stickers. The recommended stickers are then presented in a user interface to the first end-user, allowing the first end-user to select a sticker for use in replying to the received media content item. To generate the selection of recommended stickers, in response to receiving the media content item, the messaging application processes the media content item to identify specific attributes and characteristics (e.g., text included with the message, stickers used with the message, and other contextual metadata). The identified attributes and characteristics of the received message are then processed by a scoring model to identify the predetermined number of stickers for presenting in the reply interface as recommended reply stickers.

Systems and methods for a media content user interface. A media content provider includes storage for storing and serving video content to subscribers. The media content provider records and or otherwise stores video content from around the world. Subscribers are provided a user interface to the system that includes a side bar. The user interface provides context sensitive hints to assist the viewer. The system also tracks a viewer's viewing history in a manner that allows the viewer to review and directly access any part of that history. Finally, magnetic points are created for use during video scrubbing to intelligently select relocation points for the current playback position.

According to embodiments of the disclosure, methods, apparatuses, devices and storage medium for content presentation are provided. The method includes: presenting a set of media content items on a content presentation page; switching between a plurality of viewing modes based on a mode switching operation for the plurality of viewing modes, the set of media content items being presented in a plurality of different sizes in the plurality of viewing modes; and in response to switching to at least one predetermined viewing mode of the plurality of viewing modes, presenting the set of media content items and information associated with the set of media content items together. In this way, the efficiency of viewing media content can be improved, the diversified demands of users for viewing modes can be met, and the user experience can be improved.