Detecting repeating content in broadcast media
View Patent ↗Systems, methods, devices, and computer program products provide social and interactive applications for detecting repeating content in broadcast media. In some implementations, a method includes: generating a database of audio statistics from content; generating a query from the database of audio statistics; running the query against the database of audio statistics to determine a non-identity match; if a non-identity match exists, identifying the content corresponding to the matched query as repeating content.
1. A method executed by one or more computing devices, the method comprising:
determining a current match between an audio descriptor and a first reference descriptor, the current match occurring at a current time step and being associated with a current confidence score, the current time step having a time step length;
performing post-match processing, including:
determining a previous match between the audio descriptor and a second reference descriptor, the previous match occurring at a previous time step and being associated with a previous confidence score, the previous time step having the time step length; and
applying the following formula, upon condition that C h −1/L>C 0 , to the previous match and the previous confidence score:
{ M 0 ,C 0 }={M h ,C h −l/L}
where:
M 0 is a match for selecting content related to the audio descriptor;
C 0 is the current confidence score;
M h is the previous match occurring at the previous time step;
C h is the previous confidence score associated with the previous match;
l is a time step length; and
L is an expected dwell time;
selecting content related to the audio descriptor based on the match M 0 ; and
removing the selected content from a presentation to a user.
2. The method of claim 1 , where the first reference descriptor and second reference descriptor are frame descriptors.
3. The method of claim 1 , where the current match is a non-identity match.
4. The method of claim 1 , where determining the current match includes:
generating a short list of candidate auditory matches using hashing techniques; and
validating the candidate auditory matches using a validation procedure.
5. The method of claim 1 , where at least one of the previous confidence score or the current confidence score is a log likelihood confidence score given by an audio fingerprinting process.
6. A system, comprising:
a memory;
one or more processors configured to perform operations comprising:
determining a current match between an audio descriptor and a first reference descriptor, the current match occurring at a current time step and being associated with a current confidence score, the current time step having a time step length;
performing post-match processing, including:
determining a previous match between the audio descriptor and a second reference descriptor, the previous match occurring at a previous time step and being associated with a previous confidence score, the previous time step having the time step length; and
applying the following formula, upon condition that C h −1/L>C 0 , to the previous match and the previous confidence score:
{ M 0 ,C 0 }={M h ,C h −l/L}
where:
M 0 is a match for selecting content related to the audio descriptor;
C 0 is a the current confidence score;
M h is the previous match occurring at the previous time step;
C h is the previous confidence score associated with the previous match;
l is a time step length; and
L is an expected dwell time;
selecting content related to the audio descriptor based on the match M 0 ; and
removing the selected content from a presentation to a user.
7. The system of claim 6 , the operations further comprising:
validating the current match using non-auditory information.
8. The system of claim 6 , the operations further comprising:
determining end points of the repeating content.
9. The system of claim 8 , where the end points are determined using dynamic programming techniques.
10. The system of claim 6 , the operations further comprising:
applying metrics to the selected content to determine if the repeating content is an advertisement.
11. The system of claim 10 , where the metrics are from a group of metrics consisting of time duration, volume, visual activity, and blank frame bracketing.
12. The system of claim 6 , where the first reference descriptor and second reference descriptor are generated from ambient audio snippets of a media broadcast.
13. The system of claim 6 , where the first reference descriptor and second reference descriptor are frame descriptors.
14. The system of claim 6 , where the current match is a non-identity match.
15. The system of claim 14 , where the non-identity match is determined using hashing techniques.
16. The system of claim 6 , where at least one of the previous confidence score or the current confidence score is a log likelihood confidence score given by an audio fingerprinting process.
17. A non-transitory computer-readable storage medium having instructions stored thereon, which, when executed by a processor, causes the processor to perform operations comprising:
determining a current match between an audio descriptor and a first reference descriptor, the current match occurring at a current time step and being associated with a current confidence score, the current time step having a time step length;
performing post-match processing, including:
determining a previous match between the audio descriptor and a second reference descriptor, the previous match occurring at a previous time step and being associated with a previous confidence score, the previous time step having the time step length; and
applying the following formula, upon condition that C h −1/L>C 0 , to the previous match and the previous confidence score:
{ M 0 ,C 0 }={M h ,C h −l/L}
where:
M 0 is a match for selecting content related to the audio descriptor;
C 0 is the current confidence score;
M h is the previous match occurring at the previous time step;
C h is the previous confidence score associated with the previous match;
l is a time step length; and
L is an expected dwell time;
selecting content related to the audio descriptor based on the match M 0 ; and
providing the selected content for a presentation to a user.
18. The medium of claim 17 , the operations further comprising:
applying at least one metric to the selected content to determine if the repeating content is an advertisement.
19. The medium of claim 18 , wherein the metric is associated with one of a length of a media broadcast and a volume of a media broadcast.
20. The medium of claim 17 , where at least one of the previous confidence score or the current confidence score is a log likelihood confidence score given by an audio fingerprinting process.
21. A method executed by a computer, the method comprising:
determining a current match between an audio descriptor and a first reference descriptor, the current match occurring at a current time step and being associated with a current confidence score, the current time step having a time step length;
determining a previous match between the audio descriptor and a second reference descriptor, the previous match occurring at a previous time step and being associated with a previous confidence score, the previous time step having the time step length;
discounting the previous confidence score by a discount value, the discount value being calculated based on a ratio between the time step length and an expected dwell time;
determining that the discounted previous confidence score is greater than the current confidence score;
selecting content related to the audio descriptor based on the previous match; and
removing the selected content from a presentation to a user.
22. The method of claim 21 , where the current match is a non-identity match.
23. The method of claim 21 , where the expected dwell time indicates an expected time between channel changes.
24. The method of claim 21 , wherein the previous match is a best match of the previous time step.
25. The method of claim 24 , wherein each of the current confidence score and the previous confidence score includes a log-likelihood confidence score given by an audio fingerprinting process.
26. A system, comprising:
a processor; a memory;
one or more computers configured to perform operations comprising:
determining a current match between an audio descriptor and a first reference descriptor, the current match occurring at a current time step and being associated with a current confidence score, the current time step having a time step length;
determining a previous match between the audio descriptor and a second reference descriptor, the previous match occurring at a previous time step and being associated with a previous confidence score, the previous time step having the time step length;
discounting the previous confidence score by a discount value, the discount value being calculated based on a ratio between the time step length and an expected dwell time;
determining that the discounted previous confidence score is greater than the current confidence score;
selecting content related to the audio descriptor based on the previous match; and
removing the selected content from a presentation to a user.
27. The system of claim 26 , wherein the current match is a non-identity match.
28. The system of claim 26 , wherein the expected dwell time indicates an expected time between channel changes.
29. The system of claim 26 , wherein the previous match is a best match of the previous time step.
30. The system of claim 29 , wherein each of the current confidence score and the previous confidence score includes a log-likelihood confidence score given by an audio fingerprinting process.
31. A computer program product tangibly stored on a non-transitory computer-readable storage medium and operable to cause one or more computers to perform operations comprising:
determining a current match between an audio descriptor and a first reference descriptor, the current match occurring at a current time step and being associated with a current confidence score, the current time step having a time step length;
determining a previous match between the audio descriptor and a second reference descriptor, the previous match occurring at a previous time step and being associated with a previous confidence score, the previous time step having the time step length;
discounting the previous confidence score by a discount value, the discount value being calculated based on a ratio between the time step length and an expected dwell time;
determining that the discounted previous confidence score is greater than the current confidence score;
selecting content related to the audio descriptor based on the previous match; and
removing the selected content from a presentation to a user.
32. The product of claim 31 , wherein the current match is a non-identity match.
33. The product of claim 31 , wherein the expected dwell time indicates an expected time between channel changes.
34. The product of claim 31 , wherein the previous match is a best match of the previous time step.
35. The product of claim 34 , wherein each of the current confidence score and the previous confidence score includes a log-likelihood confidence score given by an audio fingerprinting process.