2682 results about "Media content" patented technology

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 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.

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.

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.

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.

Generative media content (e.g., generative audio) can be dynamically generated based on various inputs, which can include blockchain data. A playback device accesses blockchain data stored via a distributed ledger and generates media content based at least in part on the blockchain data. The playback device can access a library of pre-existing media segments and arrange a selection of pre-existing media segments from the library for playback according to a generative media content model and based at least in part on the blockchain data. The generated media content can then be played back via the playback device.

A recommendation system is described, which identifies engaged fans for an artist and requests input from the engaged fans regarding a collaboration by the artist with at least one different artist. In implementations, engaged fans are identified as having user profiles on a media content platform that satisfy at least one threshold engagement criteria based on consumption of at least one media content item associated with the artist. The recommendation system presents a user interface that includes at least one prompt for feedback that enables engaged fans to recommend how the artist collaborate with others. In some implementations, the user interface includes controls that are selectable to define artist characteristics to feature in a collaboration and the recommendation system is configured to generate a synthesized collaboration by automatically combining different artists' characteristics using a trained machine learning model. Recommendations based on engaged fan feedback are then provided to artists.

Certain aspects of the disclosure provide artificial intelligence (AI) methods and systems for generating personalized social media content with trend integration. A method generally includes retrieving data from data sources that includes customer interactions with a business, and inventory data of the business, determining trending-product pairs that increase engagement of the customers with products recorded in the inventory data of the business based on the retrieved data. A generative artificial intelligence (AI) model is used to generate one or more of a caption, a hashtag, and a promotional image that are personalized to each of the customers in response to receiving prompts that contain information about the customers, information about trending-product pairs, and social media platforms of the customers. The method sends one or more of the captions, the hashtags, and the promotional images that are personalized to the customers to social media platforms of the customers.

The embodiment of the invention provides a content display method and device, equipment, a computer readable storage medium and a product, and the method comprises the steps: responding to a first operation triggered by a user for a first theme, and displaying a first display interface associated with the first theme; first content is displayed in the first display interface, the first content comprises media content associated with the first theme and multiple pieces of third content associated with second content, and the second content is generated based on the first theme; and in response to a second operation of the user in the first display interface, displaying a second display interface associated with the first theme, the second display interface being used for displaying the second content. Therefore, the display content in the first display interface can be enriched, so that a user can check more abundant related content of the first theme in the first display interface. In addition, the second user can check the second content in the second display interface more visually.

Network services encode multimedia content, such as video, into multiple adaptive bitrate streams of encoded video and a separate trick play stream of encoded video to support trick play features. The trick play stream is encoded at a lower encoding bitrate and frame rate than each of the adaptive bitrate streams. The adaptive bitrate streams and the trick play stream are stored in the network services. During normal content streaming and playback, a client device downloads a selected one of the adaptive bitrate streams from network serviced for playback at the client device. To implement a trick play feature, the client device downloads the trick play stream from the network services for trick play playback.

The invention relates to the technical field of data processing, and discloses a film and television supervision analysis method and system based on data mining and a storage medium. The method comprises the following steps: collecting film and television data in a panoramic manner, and carrying out cross-media transcoding processing to obtain a multi-dimensional data set; performing video semantic extraction, audio emotion recognition and text tendency analysis on the data set to generate a time sequence mark list; scoring the key elements according to social influence, propagation depth and audience acceptability to form a dynamic score table; analyzing the propagation path based on the score table, and constructing an influence map; sorting supervision points according to the atlas, and making an intelligent supervision scheme; the execution deviation is analyzed through effect feedback, and the supervision parameters are optimized. According to the method, multi-dimensional content feature extraction, social influence evaluation and propagation path analysis of the film and television works are realized in a mass multimedia content environment, a precise and differentiated intelligent supervision scheme is formed, and the method has self-optimization and adjustment capabilities at the same time.

A technique for resource allocation estimation for media content items is described. In accordance with the described techniques engagement by a set of user accounts with respective media content items of at least one media content service provider system is obtained. The media content service provider system and / or a payment service system generates historical streaming data for the respective media content items based on the engagement of the set of user accounts. An estimated streaming count of a media content item over a time period based on the historical streaming data for the respective media content items is determined. An estimated resource allocation for the artist is determined based on the estimated streaming count and an advance of funds is facilitated based on the estimated resource allocation to an account of the artist during the time period.

The invention discloses a private network content copyright monitoring and evidence obtaining system based on AI and a large model, which utilizes AI and large model technologies to carry out copyright monitoring and evidence obtaining on multimedia content in a private network environment, and carries out deep semantic understanding and cross-modal feature extraction through a large model processor to generate unified semantic representation. The method comprises the steps that a copyright content database is established and stored in a copyright content knowledge base, the copyright content knowledge base is used for storing metadata of original content protected by copyright, unified semantic representation and copyright declarations in a natural language form provided by a copyright party, and the copyright declarations are converted into query vectors through a semantic understanding technology; the method comprises the following steps: acquiring a semantic representation of a multimedia content, performing similarity calculation with the semantic representation of the multimedia content, identifying infringement content, when the infringement content is identified, recording an original source, publishing time and publisher information of the infringement content, performing differentiation analysis, generating an evidence chain, displaying a copyright monitoring result through a user interface, generating infringement alarm information, and presenting details of the evidence chain.

Systems and methods for generating customized media content are provided. Data regarding engagement with customized media content may be tracked and used to train a neural network to generate a content generation module that optimize for increased engagement by adjusting parameters (weights). A new content generation module may be generated by the trained neural network based on a selected set of content attributes and generative artificial intelligence (AI) protocols. New customized media content may thereafter be generated by using the new video content generation module to incorporate multi-modal fusion of facial expression data into video content for the new customized media content based on the selected set of content attributes, use voice matching algorithms to generate an audio track for the video content, synchronize the audio track to the video content, and integrate one or more of the selected set of content attributes into the new customized media content.

The invention provides a commodity multimedia recommendation method and system combined with RPA and AI.The method comprises the steps that firstly, a current interaction behavior flow of a user and a commodity multimedia interface is recorded in real time through an RPA interaction capture module, the current interaction behavior flow comprises an operation triggering time sequence and an attention staying track, then an intention evolution track is extracted based on a preset historical interaction mode library, and the intent evolution track is extracted; the method comprises the following steps of: generating a dynamic matching rule set according to an intention evolution track, including an association constraint condition and a priority ranking logic, inputting the dynamic matching rule set into a pre-trained AI recommendation model, performing rule matching screening on a candidate commodity multimedia content set, generating a screening result, and outputting the screening result to a user. And finally, a recommendation sequence is rendered in real time according to a screening result through an RPA display arrangement module, and the display size and the text typesetting style are adjusted, so that the individuation degree of commodity multimedia recommendation and the user experience are improved.

A system including a media data optimization engine (MDOE) and a method for automatically creating structured data objects for media content rendered in one or more languages in an electronic document of a business entity are provided. The MDOE identifies non-textual objects including media content rendered in one or more languages in the electronic document and generates textual objects in the corresponding language(s) therefrom. The MDOE transforms the textual objects into structured data objects based on configurable criteria and generates a dynamic index-oriented object for the structured data objects specific to the business entity. The MDOE connects the structured data objects to the dynamic index-oriented object by creating linked data nodes therefrom with the dynamic index-oriented object as a core. The MDOE connects the dynamic index-oriented object with the linked data nodes to the electronic document, thereby facilitating dynamic changes to the electronic document and dynamically optimizing the electronic document.

The invention provides an artificial intelligence semantic processing system and method oriented to digital media creation, and relates to the technical field of artificial intelligence semantic process.The artificial intelligence semantic processing method comprises the steps that predicate argument relation pairs of language texts are extracted, object space relation pairs of sketch images are extracted at the same time, and a basic semantic unit set is constructed; the integrity and accuracy of cross-modal semantic understanding are ensured, further, semantic units are clustered by using a dynamic routing algorithm, a semantic concept cluster with a clear importance weight is generated, deep mining and structured representation of creation intentions are realized, and the creation intentions are quickly and accurately understood. An initial semantic relation graph is constructed, a graph attention network is used for dynamic reweighting, finally, an enhanced dynamic semantic graph is generated, complex association and a hierarchical structure between semantic concepts are effectively captured, finally, hierarchical analysis is carried out on the semantic graph, and a structured semantic blueprint is output, so that the dynamic semantic graph is obtained. And a reliable semantic processing technology is provided for creation of high-quality digital media contents.

The embodiment of the invention provides a media editing method and device, equipment and a storage medium. The method comprises the following steps: displaying a first sub-lens component in a sub-lens editing area of an editing interface; displaying a media generation area in the editing interface in response to a preset operation received in the first sub-lens assembly; on the basis of parameter information acquired in the media generation area, generating a first sub-lens section corresponding to the first sub-lens assembly; and displaying the first sub-lens segment in a content preview area of the editing interface. In this way, according to the embodiment of the invention, the corresponding segment of the media content can be efficiently edited through the sub-mirror component, so that the media editing efficiency is improved.

The subject technology receives frames of a source media content. The subject technology detects from the frames of the source media content, a first gesture indicating a cut point at a particular frame of the source media content, the cut point associated with a trimming operation to be performed on the source media content. The subject technology selects a starting frame and an ending frame from the frames based at least in part on the cut point at the particular frame. The subject technology performs the trimming operation based on the starting frame and the ending frame. The subject technology generates a second media content using the third set of frames. The subject technology provides for display at least a portion of the third set of frames of the second media content.

A playback device is configured to (i) operate as part of a synchrony group including at least one other group member, (ii) obtain a respective indication of each group member's capability to play back media content, (iii) based on the respective indications, determine a group capability to play back media content, (iv) transmit, to a cloud-based computing system, a request for a media item, (v) receive, from the cloud-based computing system, a list of different renditions of the requested media item, the list including a respective media item identifier usable to obtain each different rendition, (vi) select a rendition of the requested media item that corresponds to the determined group capability, (vii) use a media item identifier corresponding to the selected rendition to retrieve the selected rendition of the requested media item, and (viii) play back the selected rendition in synchrony with the at least one other group member.

Embodiments described herein provide for a voice biometrics system execute machine-learning architectures capable of passive, active, continuous, or static operations, or a combination thereof. Systems passively and / or continuously, in some cases in addition to actively and / or statically, enrolling speakers as the speakers speak into or around an edge device (e.g., car, television, radio, phone). The system identifies users on the fly without requiring a new speaker to mirror prompted utterances for reconfiguring operations. The system manages speaker profiles as speakers provide utterances to the system. Machine-learning architectures implement a passive and continuous voice biometrics system, possibly without knowledge of speaker identities. The system creates identities in an unsupervised manner, sometimes passively enrolling and recognizing known or unknown speakers. The system offers personalization and security across a wide range of applications, including media content for over-the-top services and IoT devices (e.g., personal assistants, vehicles), and call centers.

A system and method for multimodal latent hyperspace navigation that enables efficient compression and interactive exploration of spatiotemporal and spectral media content. The system encodes video data into a structured seven-dimensional hyperspace spanning spatial coordinates, temporal progression, viewing orientation, scale, and spectral wavelength using variational autoencoders that generate locally Lorentzian latent patches. Navigation through the hyperspace is achieved via learned geodesic transition functions guided by a latent-space metric tensor, while generative fill-in modules synthesize content for sparsely populated regions. The architecture supports real-time deployment on resource-constrained devices such as set-top boxes through efficient latent decoding and optional generative refinement. Applications include immersive film exploration with continuous zoom and viewpoint control, surveillance systems with anomaly detection capabilities, and hyperspectral environmental monitoring with real-time spectral analysis across multiple wavelength bands.

A control device such as a mobile device can be used as a secondary display to provide a controller user interface (UI) element corresponding to a contextual display user interface element displayed via a television or other device. An example method includes receiving a media data stream from a media content provider and transmitting the media data stream to a display device for playback. After determining that the media data stream comprises a contextual display user interface element, the method involves causing the controller device to present a controller user interface element corresponding to the contextual display user interface element. An indication of a user input via the controller user interface element is received, after which a signal is transmitted to the media provider that corresponds to the received indication of user input.

The present disclosure provides an image processing method, an electronic device and a readable storage medium. The method includes: obtaining identification information by identifying an identification pattern in a media image; obtaining virtual information corresponding to media content displayed in the media image according to the identification information; obtaining an image acquired in real time; and obtaining a three-dimensional image based on the virtual information and the image acquired in real time.

The invention discloses a multimedia content preloading method based on vehicle cloud collaboration, and particularly relates to the technical field of multimedia content preloading, and the method comprises the steps: carrying out the modeling through a multi-dimensional space-time driving path, and combining with historical road communication coverage features; a network availability prediction result and a user historical consumption mode are deeply mapped, and a weight fusion mechanism of content timeliness, capacity characteristics and scene correlation is introduced, so that a generated multi-level priority sequence better meets the instant requirements of vehicles at different time and different positions; through dynamic comparison of an initial plan, a real-time path, a network and user interaction data, a superposition out-of-control situation of prediction deviation can be rapidly identified, a scheduling priority offset mode under multiple tasks is identified in combination with vehicle calculation, caching and bandwidth occupation states, and then a pre-loading dislocation cooperative imbalance fault network is constructed through bidirectional correlation analysis. And visual diagnosis and quantitative evaluation of the imbalance state of the prediction layer and the execution layer are realized.

The embodiment of the invention relates to an interface interaction method and device, equipment and a storage medium. The method comprises the following steps: presenting a first viewing interface of a shooting position; and in the first viewing interface, presenting a group of interactive contents associated with the shooting position, the group of interactive contents at least comprising a first interactive content, the first interactive content being associated with a first media content, and the first media content being published in association with the shooting position. In this way, the information display efficiency of the viewing interface associated with the shooting position can be improved.

In multimedia object tracking and merging of tracked objects, an object is tracked through frames of multimedia content until a frame appears in which the tracked object is not detected. A first track is designated as one or more consecutive frames in which the tracked object is detected, the first track ending at the first frame. Tracking continues to try to detect the tracked object in a second frame subsequent to the first frame. If the tracked object is not again detected, information about the first track is output. If the tracked object is detected subsequently, a second track of consecutive tracked object detection is designated. The tracked objects in the two tracks are then compared with the aid of trained data models, and a matching score is determined to reflect the degree of match. If the matching score meets or exceeds a first threshold, the compared tracks are merged using the same identifier assigned to both tracks. If the matching score does not exceed a second threshold that is less than the first threshold, the tracks may be discarded as showing no match. If the matching score falls between the first and second thresholds, an indication is output for further analysis of the compared tracked objects.

The invention provides a self-media content streaming matching method and system based on dynamic semantic analysis, and the method comprises the steps: carrying out the dynamic semantic analysis of the text content of a voice stream of a creator, generating a semantic theme sequence, aligning the semantic theme sequence with an emotion fluctuation curve of the voice stream of the creator, and generating an emotion semantic incidence matrix; dividing a mapping relationship between an emotional intensity numerical range in the emotional fluctuation curve and a semantic topic type in the semantic topic sequence; performing behavior association fitting on the mapping relationship based on user historical feedback behavior data, and generating a dynamic association rule between the emotion intensity numerical range and the user feedback behavior; and adjusting a preset self-media content delivery strategy in real time, and generating an adjusted delivery strategy so as to carry out self-media content delivery stream matching. According to the method, the emotion semantic association matrix is constructed, accurate space-time matching of the content theme and the emotion expression is realized, and the target of adaptively optimizing the flow casting matching according to the real-time emotion state of the creator is achieved.