Methods and apparatus for improving speech recognition accuracy in media content searches are described. An advertisement for a media content item is analyzed to identify keywords that may describe the media content item. The identified keywords are associated with the media content item for use during a voice search to locate the media content item. A user may speak the one or more of the keywords as a search input and be provided with the media content item as a result of the search.

A device, system and method for providing indications of a discrepancy between a video and a textual description of an incident. A public-safety computing device determines a discrepancy between a video of an incident and a textual description of the incident, the textual description being a component of a public-safety incident report associated with the incident. The device, in response to determining the discrepancy, controls a notification device to provide an indication of the discrepancy.

A method for processing video data includes: acquiring a target segment of video data to be extracted; acquiring theme information to be extracted; and determining an association degree between the target segment and the theme information based on segment information of the video data and a relationship between the target segment and the video data.

The present disclosure provides a video timing labeling method. The method includes: acquiring a video file to be labeled and text information to be inquired; acquiring a video segment matching the text information to be inquired based on a timing labeling network of a timing labeling model; acquiring a video feature of the video segment matching the text information to be inquired based on a feature extraction network of the timing labeling model; acquiring text information corresponding to the video segment labeled in the video file based on a visual text translation network of the timing labeling model; and outputting the video segment matching the text information to be inquired and the text information corresponding to the video segment labeled in the video file based on the timing labeling model.

A method and a system for retrieving video temporal segments are provided. In the method, a video is analyzed to obtain frame feature information of the video; the frame feature information is input into an encoder to output first data relating to temporal information of the video; the first data and a retrieval description for retrieving video temporal segments of the video are input into a decoder to output second data; attention computation training is conducted according to the first data and the second data; video temporal segments of the video corresponding to the retrieval description are determined according to the attention computation training.

Systems and methods are provided for distributed video storage and search over edge computing devices having a short-term memory and a long-term memory. The method may comprise caching a first portion of data on a first device. The method may further comprise determining, at a second device, whether the first device has the first portion of data. The determining may be based on whether the first piece of data satisfies a specified criterion. The method may further comprise sending the data, or a portion of the data, and/or a representation of the data from the first device to a third device.

One or more frames sampled from a first media item of an event are analyzed to identify one or more candidate event periods within the one or more frames. For each of the one or more frames, whether a candidate event period of the one or more candidate event periods satisfies one or more conditions is determined. Responsive to determining that the candidate event period of the one or more candidate event periods satisfies the one or more conditions, the candidate event period is identified as an actual event period used to divide a time the event. Mapping data that maps the actual event period to a timestamp associated with a respective frame of the one or more frames of the first media item is generated.

A method and system for identifying social trends are provided. The method includes collecting multimedia content from a plurality of data sources; gathering environmental variables related to the collected multimedia content; extracting visual elements from the collected multimedia content; generating at least one signature for each extracted visual element; generating at least one cluster of visual elements by clustering at least similar signatures generated for the extracted visual elements; correlating environmental variables related to visual elements in the at least one cluster; determining at least one social trend by associating the correlated environmental variables with the at least one cluster.

Embodiments relate to systems, processes and devices for an information delivery platform or data hub with an alert processor that can be configured to receive a request to generate an alert configuration at the data hub, the request indicating a target unit; generate and store an alert rule corresponding to the alert configuration, the alert rule having a trigger and an action; detect an event at the data hub based on a set of data of the data stored at the data hub, the event having event data; convert the event data to an alert trigger at the data hub based on the trigger of the alert rule; generate an alert notification for the alert trigger based on the action of the alert rule; and transmit the alert notification to the target unit.

A method for automatic metadata tag identification for videos is described. Content features are extracted from a video into respective data structures. The extracted content features are from at least two different feature modalities. The respective data structures are encoded into a common data structure using an encoder of a recurrent neural network (RNN) model. The common data structure is decoded using a decoder of the RNN model to identify content platform metadata tags to be associated with the video on a social content platform. Decoding is based on group tag data for users of the social content platform that identifies groups of the users and corresponding group metadata tags of interest for the groups of users.