A system and method for generating an interface for providing recommendations based on contextual insights, the method including: generating at least one signature for at least one multimedia content element identified within an interaction between a plurality of users; generating at least one contextual insight based on the generated at least one signature and user interests of the plurality of users, wherein each contextual insight indicates a current user preference; searching for at least one content item that matches the at least one contextual insight; and generating an interface for providing the at least one content item within the interaction between the plurality of users.

A system and method for generating an interface for providing recommendations based on contextual insights, the method including: generating at least one signature for at least one multimedia content element identified within an interaction between a plurality of users; generating at least one contextual insight based on the generated at least one signature and user interests of the plurality of users, wherein each contextual insight indicates a current user preference; searching for at least one content item that matches the at least one contextual insight; and generating an interface for providing the at least one content item within the interaction between the plurality of users.

The current embodiments relate to a real-time automated classification system that uses machine learning system to recognize important moments in broadcast content based on log data and/or other data received from various classification systems. The real-time automated classification system may be trained to recognize correlations between the various log data to determine key moments in the broadcast content. The real-time automated logging system may determine and generate metadata that describe or give information about what is happening or appearing in the broadcast content. The real-time automated logging system may automatically generate control inputs, suggestions, recommendations, and/or edits relating to broadcast content based upon the metadata, during broadcasting of the broadcast content.

A scientific system and methods are disclosed for optimizing television (e.g., “CTV” and “OTT”) advertising and related expenditure to maximize efficiency and return on investment (“ROI’) for advertisers. The scientific system comprises an initial-feedback engine that develops and refines creatives or outcomes by creating and using an artificial intelligence (“AI”) engine that creates an initial feedback loop from social media platforms and subsequently uses an intelligent advertisement-selection engine that takes the highest performing advertising on the social media platforms and directs or imports them for connected television or over-the-top advertising. The system includes a performance engine that optimizes performance of the connected television and over-the-top advertising and then moves the winning combination of a creative or outcome resulting from the application inventory, the audience segment, the part of day, the frequency or the like to linear television purchase actions.

The present invention enables detection of a sponsorship credit display in a broadcast program with higher precision. A sponsorship credit display detection device 100 according to the present invention includes: a CM segment detection unit 120 that extracts a cut point, which is a time point where a frame in which the volume of an audio signal of a broadcast program is less than a volume threshold value and the amount of change from a previous frame is at least a pixel change threshold value is played, and detects a CM segment by comparing an interval of the extracted cut point with a CM defined length; a sponsorship credit display segment estimation unit 130 that estimates, as a sponsorship credit display segment, a predetermined time period before or after at least one continuous CM segment detected by the CM segment detection unit 120; and an output unit 140 that outputs information indicating the sponsorship credit display segment.

The present invention enables detection of a sponsorship credit display in a broadcast program with higher precision. A sponsorship credit display detection device 100 according to the present invention includes: a CM segment detection unit 120 that extracts a cut point, which is a time point where a frame in which the volume of an audio signal of a broadcast program is less than a volume threshold value and the amount of change from a previous frame is at least a pixel change threshold value is played, and detects a CM segment by comparing an interval of the extracted cut point with a CM defined length; a sponsorship credit display segment estimation unit 130 that estimates, as a sponsorship credit display segment, a predetermined time period before or after at least one continuous CM segment detected by the CM segment detection unit 120; and an output unit 140 that outputs information indicating the sponsorship credit display segment.

In one aspect, an example method includes (i) while a media playback device of a vehicle is playing back content received on a first channel, generating, by the media playback device, a query fingerprint using second content received on a second channel; (ii) sending, by the media playback device, the query fingerprint to a server that maintains a reference database containing a plurality of reference fingerprints; (iii) receiving, by the media playback device from the server, identifying information corresponding to a reference fingerprint of the plurality of reference fingerprints that matches the query fingerprint; and (iv) while the media playback device is playing back the first content received on the first channel, providing, by the media playback device for display, at least a portion of the identifying information.

Methods and apparatus to audio watermarking and watermark detection and extracted are described herein. Disclosed example methods to decode a watermark from an audio signal include averaging a second sequence of audio samples stored in a buffer with a first sequence of audio samples stored in the buffer to determine an averaged sequence of audio samples, the second sequence of audio samples being related to the first sequence of audio samples based on a repetition period associated with watermark data of the watermark to be decoded. Disclosed example methods also include determining whether to enable a stacker. Disclosed example methods further include, in response to the stacker being enabled, decoding the watermark from the averaged sequence of audio samples, and in response to the stacker being disabled, decoding the watermark from the first sequence of audio samples.

Methods and apparatus to audio watermarking and watermark detection and extracted are described herein. Disclosed example methods to decode a watermark from an audio signal include averaging a second sequence of audio samples stored in a buffer with a first sequence of audio samples stored in the buffer to determine an averaged sequence of audio samples, the second sequence of audio samples being related to the first sequence of audio samples based on a repetition period associated with watermark data of the watermark to be decoded. Disclosed example methods also include determining whether to enable a stacker. Disclosed example methods further include, in response to the stacker being enabled, decoding the watermark from the averaged sequence of audio samples, and in response to the stacker being disabled, decoding the watermark from the first sequence of audio samples.

A method of processing media output events, each having a corresponding duration, from a plurality of media content receivers within a media distribution system, comprises: a. dividing the output events into a plurality of segments, such that output events having similar properties are placed into the same one of said segments; b. within each said segment, identifying a long duration threshold based on the distribution of the durations of the output events within that segment; c. and applying the long duration thresholds of each said segment for control and/or analysis of the media distribution system.