Various embodiments described herein support or provide for annotation of a media asset, such as an audio asset or a video asset, based on one or more events identified within content of the media asset. In particular, some embodiments can determine one or more of the following details with respect to content of a given media asset, which can represent annotations that enable determination of contextual information for the given media asset: events; event classification labels for events; subclassifications labels for events; scenes comprising events; attributes of scenes; themes presented by the content; and title-level attributes of the given media asset.

The disclosed embodiments are directed toward local emotion detection during live streaming events. A client device receives a video stream from a remote server and captures media content while displaying the video stream. The client device uses a local machine learning/artificial intelligence event detection model to detect events in the media content. The client device then transmits detected events to the remote server involved in the live stream. The client device may additionally stream the locally captured media content to the remote server. In response, the remote server provides an interaction dashboard and, in some embodiments, mixes the local media content with the live stream.

A method for improving a user experience through the use of at least one communications device. The method initially senses feedback of the user experience, wherein the user experience include one or more of the following three dimensional geolocation status, temporal status, experiential status, physiological status and emotional status. The method creates at least an initial contextual data set from the initially sensed feedback, and transmits media content to the user. The method subsequently senses feedback of the user experience, creating one or more subsequent contextual data set from the subsequent sensed feedback. The method measures changes in the user experience by comparing the initial contextual data set with the subsequent contextual data set. The method generates personalized user data based on measuring changes, wherein the generated personalized data is indicative of adjustments in one or more of the three dimensional geolocation, experiential status, physiological status and emotional status of the user when the comparing of the initial contextual data set with the subsequent contextual data set.

The present disclosure provides a video data processing method and device, and a readable storage medium, where the technical means is adopted which includes: processing, according to a preset trained deep learning algorithm model, input video data to be processed, to obtain a label vector of the video data; determining, according to a label vector of each music data in a music library and a preset recommendation algorithm, a recommendation score of the label vector of each music data with respect to the label vector of the video data; and taking, according to the each recommendation score, the music data matching the video data as background music. By means of the above, and further a deep learning algorithm model and a recommendation algorithm, the data processing efficiency of finding the background music of the video data in the music library is effectively improved, and the labor cost is reduced.

In various embodiments, a Data Processing System for Generating Interactive User Interfaces and Interactive Game Systems Based on Spatiotemporal Analysis of Video Content may be configured to: (1) enable a user to select one or more players participating in a substantially live (e.g., live) sporting or other event; (2) determine scoring data for each of the one or more selected players during the sporting or other event; (3) track the determined scoring data; (4) generate a custom (e.g., to the user) user interface that includes the scoring data; and (5) display the custom user interface over at least a portion of a display screen (e.g., on a mobile computing device) displaying one or more video feeds of the sporting or other event. In this way, the system may be configured to convert a video feed of a sporting event into an interactive game.

Methods, systems, and non-transitory, machine-readable media are disclosed for audio adaption of content items to device operations of an endpoint media device. First observation data corresponding to media device operations associated with a first media device and mapped to first content items may be processed. A first content composite including an adaptable content item may be received. The first content composite may be adapted with a first audio segment. Based on the first observation data, the first audio segment may be selected. The first content composite may be configured with the first audio segment so that the adapted first content composite plays the first audio segment when the adapted first content composite is presented. The adapted first content composite may be output for presentation, where the first endpoint media device or the second endpoint media device performs at least one operation relating to the adapted first content composite.

A method for determining location of a premises is disclosed. The method includes measuring a signal strength of a plurality of communication signals received at the premises, obtaining data associated with a source of the signals, estimating a propagation loss for the received signal, determining a distance between a source of each of the signals and the premises based on the estimated propagation loss, and triangulating the location of the premises.

As described herein, a machine learning system, method, and computer program are provided to predict which resident of a residential space is watching television for content targeting purposes. In use, a login to a television service on a television device in a residential space is detected. Additionally, information defining a plurality of residents of the residential space is identified. Further, a profile determined for the login is identified, where the profile is associated with a particular resident of the plurality of residents or a particular resident group of the plurality of residents. Still yet, the profile and the information defining the plurality of residents of the residential space is input to a machine learning model to predict one or more residents of the plurality of residents that is consuming the television service on the television device.

According to the present disclosure, there is provided a method and platform of generating a short video, an electronic device and a storage medium, which relates to a field of video processing. The method includes: receiving at least one video material clip; obtaining a feature information of a user; and generating the short video based on the at least one video material clip, according to the feature information of the user.

Systems and methods are described herein for recommending content restrictions to a user based on chatter in a social network of the user. The system analyzes chatter in the social network to identify a correlation between what is posted by users and the content that the users are posting about. The system stores a mapping between chatter and expected attributes of the content referenced by the chatter. The system will determine whether to block the content when an expected attribute is associated with a content restriction.