Real-time automated classification system
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.
1. A tangible, non-transitory machine-readable medium comprising machine-readable instructions for providing automated classification of broadcast content that, when executed by one or more processors, cause the one or more processors to:
receive log data generated during generation of the broadcast content from one or more devices associated with generation of the broadcast content;
characterize the log data, correlate the log data, or both to derive one or more features based upon the log data;
derive metadata comprising data corresponding to the broadcast content based on the derived features; and
perform automated reporting based on the metadata during broadcasting of the broadcast content, by:
determining a target based upon the metadata;
searching one or more information sources for information relating to the target;
generating a report based on results of the search; and
providing the report to authorized personnel, incorporating data related to the report into the broadcast content, or both.
2. The non-transitory machine-readable medium of claim 1 , wherein the log data comprise time code information, text information, audio log, real-time graphic system log, tally log, switcher log, newsroom system log, MOS gateway log, replay log, character generator log, video playout log, or a combination thereof.
3. The non-transitory machine-readable medium of claim 1 , wherein the metadata comprises an indication of one or more highlight moments of the broadcast content.
4. The non-transitory machine-readable medium of claim 3 , wherein the machine-readable instructions comprise instructions to, during the broadcasting of the broadcast content, generate a clip corresponding to the highlight moment of the broadcast content based on the metadata.
5. The non-transitory machine-readable medium of claim 1 , wherein the machine-readable instructions comprise instructions to comprise instructions to, during the broadcasting of the broadcast content and based on the metadata:
generate a suggestion for a graphical presentation corresponding to a current portion of the broadcast content; and
incorporate the graphical presentation into the broadcast content.
6. A machine-implemented method for providing real-time automated logging of broadcast content, comprising:
receiving log data generated during generation of the broadcast content from one or more devices associated with generation of the broadcast content;
characterizing the log data, correlating the log data, or both to derive one or more features based upon the log data;
deriving metadata comprising data indicative of what is appearing on the broadcast content; and
performing automated reporting, based on the metadata during broadcasting of the broadcast content, by:
determining a target based upon the metadata;
searching one or more information sources for information relating to the target;
generating a report based on results of the search; and
providing the report to authorized personnel, incorporating data related to the report into the broadcast content, or both.
7. The method of claim 6 , wherein the log data comprise time code information, text information, audio log, real-time graphic system log, tally log, switcher log, newsroom system log, MOS gateway log, replay log, character generator log, video playout log, or a combination thereof.
8. The method of claim 6 , comprising performing automated suggestions based on the metadata by:
generating a suggestion for a graphical presentation corresponding to a current portion of the broadcast content; and
incorporating the graphical presentation into the broadcast content.
9. The method of claim 6 , comprising performing automated suggestions by:
generating, based on the metadata, a clip corresponding to a highlight moment of the broadcast content; and
incorporating the clip into the broadcast content or into digital distribution products.
10. A tangible, non-transitory machine-readable medium comprising machine-readable instructions for providing automated classification of broadcast content that, when executed by one or more processors, cause the one or more processors to:
receive log data generated during generation of broadcast content from one or more devices associated with generation of the broadcast content;
characterize the log data, correlate the log data, or both to derive one or more features based upon the log data;
derive metadata comprising data indicative of what is appearing on the broadcast content; and
perform, during broadcasting of the broadcast content, automated control by adjusting processing of verbiage audio signals with respect to background audio signals based upon the metadata.
11. The non-transitory machine-readable medium of claim 10 , wherein the log data comprise time code information, text information, audio log, real-time graphic system log, tally log, switcher log, newsroom system log, gateway machine settings, replay log, character generator log, video playout log, or a combination thereof.
12. The non-transitory machine-readable medium of claim 10 , wherein the machine-readable instructions, when executed by the one or more processors, cause a machine learning module to be trained based on records of previous live broadcast content.
13. The non-transitory machine-readable medium of claim 10 , wherein the machine-readable instructions, when executed, cause the one or more processors to:
predict, based on the metadata, automated suggestions, automated reporting, or both; and
incorporate the predicted automated suggestions, the predicted automated reporting, or both into the broadcast content.
14. The non-transitory machine-readable medium of claim 13 , wherein the machine-readable instructions, when executed, cause the one or more processors to:
receive an approval of the predicted automated suggestions, the predicted automated reporting, or both; and
in response to receiving the approval, incorporate the predicted automated suggestions, the predicted automated reporting, or both into the broadcast content.
15. A machine-implemented method for providing real-time automated logging of broadcast content, comprising:
receiving log data generated during generation of the broadcast content from one or more devices associated with generation of the broadcast content;
characterizing the log data, correlating the log data, or both to derive one or more features based upon the log data;
deriving metadata comprising data corresponding to the broadcast content based on the derived features; and
performing, during broadcasting of the broadcast content, automated control by adjusting processing of verbiage audio signals with respect to background audio signals based upon the metadata.
16. The method of claim 15 , comprising:
performing, during the broadcasting of the broadcast content, automated suggestions by:
isolating, based upon the log data, a verbiage channel of multiple channels of audio of the broadcast content; and
generating textual data representative of verbiage present on the isolated verbiage channel, via automated speech recognition, automated translation, or both;
performing, during the broadcasting of the broadcast content, automated reporting by:
determining a target based upon the metadata;
searching one or more information sources for information relating to the target;
generating a report based on results of the search; and
providing the report to authorized personnel, incorporating data related to the report in the broadcast content, or both; or
both.
17. A tangible, non-transitory machine-readable medium comprising machine-readable instructions for providing automated classification of broadcast content, when executed by one or more processors cause the one or more processors to:
receive log data generated during generation of the broadcast content from one or more devices associated with generation of the broadcast content;
characterize the log data, correlate the log data, or both to derive one or more features based upon the log data;
derive metadata comprising data corresponding to the broadcast content based on the derived features; and
perform, based on the metadata and during broadcasting of the broadcast content, automated suggestions, by:
isolating, based upon the log data, a verbiage channel of multiple channels of audio of the broadcast content; and
generating textual data representative of verbiage present on the isolated verbiage channel, via automated speech recognition, automated translation, or both.
18. The non-transitory machine-readable medium of claim 17 , wherein the instructions, when executed, cause the one or more processors to:
perform automated control during the broadcasting of the broadcast content;
perform automated reporting during the broadcasting of the broadcast content; or
both.
19. A machine-implemented method for providing real-time automated logging of broadcast content, comprising:
receiving log data generated during generation of the broadcast content from one or more devices associated with generation of the broadcast content;
characterizing the log data, correlating the log data, or both to derive one or more features based upon the log data;
deriving metadata comprising data indicative of what is appearing on the broadcast content; and
performing, based on the metadata and during broadcasting of the broadcast content, automated suggestions, by:
isolating, based upon the log data, a verbiage channel of multiple channels of audio of the broadcast content; and
generating textual data representative of verbiage present on the isolated verbiage channel, via automated speech recognition, automated translation, or both.
20. The method of claim 19 , comprising:
performing automated control during the broadcasting of the broadcast content;
performing automated reporting during the broadcasting of the broadcast content; or
both.