3776 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.

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 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.

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.

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.

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.

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.

The invention relates to a knowledge-intensive visual question and answer automatic data generation method and device, and the method comprises the steps: constructing an original visual data set containing the professional knowledge of a target domain according to a static image, a video stream and multimedia content; extracting a representative frame sequence, converting the audio information into text information, and extracting character information in the static image to construct a structured visual instance database; according to the prompt text meeting the preset professional depth condition, establishing a three-level prompt system containing domain knowledge, an evaluation standard and a generation specification; generating a corresponding visual question and answer pair data set according to the dynamic cooperation of the main agent and the domain expert agent; generating a multi-agent quality evaluation system according to the quality evaluation result; and designing a difficulty grading mechanism according to the negative example sample. According to the method, the professionality, the accuracy and the diversity of the visual question and answer data are remarkably improved, and reliable data support is provided for training and evaluation of a multi-modal large model.

Systems and methods for a media content delivery service. A media content provider includes a data store for storing and serving media content to subscribers. The media content provider continually records and or otherwise stores video and audio content from around the world. Stored content will generally correspond to a large number of other media content providers, such as cable television operators, Internet based media content providers, television networks, and so on. Subscribers to the media provider interact with the media content provider via hardware and / or software mechanisms either provided by the media content provider or conforming to specifications of the media content provider. Based on these subscriber's subscriptions to the other content providers, the subscribers will have viewing, listening, or application execution privileges for content maintained in the data store. Content of a subscriber corresponding to multiple video content providers is maintained and served by a single provider.

A system and method for generating contextually relevant reply suggestions for media posts is disclosed. The system analyzes media content to identify visual objects, scenes, text, and metadata attributes using computer vision techniques. Identified objects and attributes are incorporated into structured prompt templates to construct detailed natural language descriptions of the media context. The prompts are provided to a text generation artificial intelligence (AI) that outputs a plurality of contextual reply suggestions based on the media analysis. Suggestions are displayed as selectable options adjacent to the media post. Users can cycle through suggestions and select a reply to send. Selections are logged to improve the AI model. Feedback on suggestion quality can also be collected. By integrating computer vision and AI generation driven by engineered prompts, the system produces highly relevant, personalized responses tailored to media content. The techniques enhance user engagement with media posts through intelligent AI reply suggestions.

A system and method for structuring and analyzing multimodal, unstructured data, as well as an article of manufacture and processor-readable storage medium implementing the same, may be used to provide a content creator with a tool to understand what actionable steps they could take to make a video perform well or go viral. Embodiments include a user interface simultaneously including a region for accepting a user query and a region that displays insight cards. The insight cards are generated based on retrieving a plurality of streaming contents, sorting the plurality of streaming contents into a viral set using one or more virality metrics, generating at least one token from the viral set, and performing a search of the viral set as a function of the at least one token to produce one or more results. The results are presented through the one or more insight cards in the user interface.

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 channel bar. The channel bar is dynamically scoped responsive to interactions of a viewer with the system. Selectable elements within the channel bar provide direct access to related content regarding video content, such as television series information and cast information. In addition, the channel bar is operable in multiple modes. An EPG mode displays live video for multiple channels simultaneously. Themed modes permit channel bars that display content according to various themes which may be defined by a viewer, the provider, or both.

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.

Method comprising: receiving, by a computing device, an indication to launch a voice-based television assistant; displaying a user interface including a prompt for receiving verbal input; receiving first voice data for a first query related to a media content recommendation; sending, by the computing device and to a server computer, the first voice data for the first query; receiving a response to the first query, the request for the additional information being based on at least one of previous queries, previous responses, or a context for the first query; and in response to receiving the response, receiving second voice data for a second query related to the media content recommendation. Method for providing a personalized description of a media content item and method for providing a trivia game related to a media content item.

Disclosed are apparatuses, systems, and techniques for efficient instance segmentation with vision language models (VLMs). In an embodiment, the techniques include processing an input into the VLM to generate a segmentation map of a media item. The input includes the media item, which includes a plurality of media item units (e.g., pixels, groups of pixels), and further includes a prompt associated with the media item. The segmentation map includes identification of media item units associated with individual objects of one or more objects in the media item, and the VLM includes a dynamic portion having parameters that are determined in view of the media item.

Machine learning based processing systems and techniques are described. In some examples, a machine learning based processing system analyzes text-based input to extract a plurality of natural language elements from the text-based input. The text-based input is associated with an object. The machine learning based processing system generates a prompt from at least a subset of the plurality of natural language elements. The machine learning based processing system analyzes the prompt by using a trained machine learning model to generate a response. The response is responsive to the prompt. The machine learning based processing system analyzes the response to extract a plurality of media content elements from the response. The plurality of media content elements corresponds to different aspects of the object.

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.

The invention relates to the technical field of data processing, can be applied to business scenes such as financial science and technology and medical health, and discloses a cross-platform information interaction method, device and equipment and a medium, and the method comprises the steps: obtaining original information sent by a source platform, and analyzing the original information into a standardized data structure according to a preset data format; extracting multimedia content elements from the structure and performing format conversion to generate standardized multimedia content; packaging the structure and the content into a to-be-transmitted data packet; acquiring network delay and bandwidth parameters of the target platform, and selecting a transmission path based on the parameters; compressing the to-be-transmitted data packet and sending the compressed to-be-transmitted data packet to the target platform through the selected path; and the target platform receives and analyzes the compressed data packet and presents the original information content. Information format compatibility is achieved through a standardized structure and content packaging, transmission efficiency is improved through network parameter perception and path selection, complete presentation of information is guaranteed in combination with compression processing and terminal adaptation, and stability and consistency of cross-platform interaction are enhanced.