Abstract: A method includes determining, at a processor of a device, an unordered match between a set of consecutive portions of a first audio fingerprint and a set of non-consecutive portions of a second audio fingerprint. The method also includes, in response to determining that a length of the unordered match satisfies a length criterion, outputting an indicator that the first audio fingerprint matches the second audio fingerprint.

Abstract: A method includes determining, at a processor of a device, an unordered match between a set of consecutive portions of a first audio fingerprint and a set of non-consecutive portions of a second audio fingerprint. The method also includes setting, based at least in part on a station associated with the second audio fingerprint, a length criterion to indicate a first length or a second length. The method further includes, in response to determining that a length of the unordered match satisfies a length criterion, outputting an indicator that the first audio fingerprint matches the second audio fingerprint.

Abstract: A method includes computing match scores for each portion of multiple portions of a first audio fingerprint. The match scores are based on a comparison of the portion with each of multiple portions of a second audio fingerprint. The method includes applying a positional penalty to a highest score of the match scores for a portion of the first audio fingerprint and generating a list of runs based on the highest score for each portion of the multiple portions of the first audio fingerprint. The method includes determining, based on the list of runs, an unordered match between a set of consecutive portions of the first audio fingerprint and a set of non-consecutive portions of the second audio fingerprint. The method includes, in response to determining that a length of the unordered match satisfies a length criterion, outputting an indicator that the first audio fingerprint matches the second audio fingerprint.

Abstract: An end user can sample a radio or television broadcast, generate a user representation of the broadcast sample, and send the user representation to a comparison system, which also receives known representations of content broadcast by multiple different stations. The known representations are stored in a continuous fashion, and represent actually broadcast content. The comparison system identifies the source of the broadcast sample by comparing the user representation to the known representations associated with each of the different stations using a bit count method, such as the Hamming distance. By comparing two representations of content that was actually broadcast, a broadcast source can be identified without requiring the use of watermarks, timestamps, or a database of discreet content items.

Abstract: An end user can sample a radio or television broadcast, generate a user representation of the broadcast sample, and send the user representation to a comparison system, which also receives known representations of content broadcast by multiple different stations. The known representations are stored in a continuous fashion, and represent actually broadcast content. The comparison system identifies the source of the broadcast sample by comparing the user representation to the known representations associated with each of the different stations using a bit count method, such as the Hamming distance. By comparing two representations of content that was actually broadcast, a broadcast source can be identified without requiring the use of watermarks, timestamps, or a database of discreet content items.

Abstract: Small changes in a broadcast version of a base media item can be identified by performing a multi-level comparison of digital fingerprints. A fingerprint of a base media item is compared to a fingerprint of a media broadcast to determine whether a media item embedded in a broadcast is likely, to a first level of certainty, to be the base media item. A second, more stringent, match between the fingerprint of the base media item and loosely matched items can be used to identify potentially-altered versions of the base media item. Potentially-altered versions can be compared against each other, and resulting matches are flagged as altered base media items, which can be fingerprinted and tested against broadcast fingerprints in the same manner as the base media item.

Abstract: Small changes in a broadcast version of a base media item can be identified by performing a multi-level comparison of digital fingerprints. A fingerprint of a base media item is compared to a fingerprint of a media broadcast to determine whether a media item embedded in a broadcast is likely, to a first level of certainty, to be the base media item. A second, more stringent, match between the fingerprint of the base media item and loosely matched items can be used to identify potentially-altered versions of the base media item. Potentially-altered versions can be compared against each other, and resulting matches are flagged as altered base media items, which can be fingerprinted and tested against broadcast fingerprints in the same manner as the base media item.

Abstract: A method includes determining, at a processor of a device, an unordered match between a set of consecutive portions of a first audio fingerprint and a set of non-consecutive portions of a second audio fingerprint. The method also includes, in response to determining that a length of the unordered match satisfies a length criterion, outputting an indicator that the first audio fingerprint matches the second audio fingerprint.

Abstract: Small changes in a broadcast version of a base media item can be identified by performing a multi-level comparison of digital fingerprints. A fingerprint of a base media item is compared to a fingerprint of a media broadcast to determine whether a media item embedded in a broadcast is likely, to a first level of certainty, to be the base media item. A second, more stringent, match between the fingerprint of the base media item and loosely matched items can be used to identify potentially-altered versions of the base media item. Potentially-altered versions can be compared against each other, and resulting matches are flagged as altered base media items, which can be fingerprinted and tested against broadcast fingerprints in the same manner as the base media item.

Abstract: An end user can sample a radio or television broadcast, generate a user representation of the broadcast sample, and send the user representation to a comparison system, which also receives known representations of content broadcast by multiple different stations. The known representations are stored in a continuous fashion, and represent actually broadcast content. The comparison system identifies the source of the broadcast sample by comparing the user representation to the known representations associated with each of the different stations using a bit count method, such as the Hamming distance. By comparing two representations of content that was actually broadcast, a broadcast source can be identified without requiring the use of watermarks, timestamps, or a database of discreet content items.

Abstract: A method includes receiving an audio fingerprint from a listening device. The method also includes, in response to determining that a portion of a stored audio fingerprint substantially matches a portion of the received audio fingerprint, identifying a longest unordered match between the received audio fingerprint and the stored audio fingerprint that satisfies a similarity threshold. The method further includes, in response to determining that the identified longest unordered match satisfies a length criterion, detecting a match between the received audio fingerprint and the stored audio fingerprint.

Abstract: Small changes in a broadcast version of a base media item can be identified by performing a multi-level comparison of digital fingerprints. A fingerprint of a base media item is compared to a fingerprint of a media broadcast to determine whether a media item embedded in a broadcast is likely, to a first level of certainty, to be the base media item. A second, more stringent, match between the fingerprint of the base media item and loosely matched items can be used to identify potentially-altered versions of the base media item. Potentially-altered versions can be compared against each other, and resulting matches are flagged as altered base media items, which can be fingerprinted and tested against broadcast fingerprints in the same manner as the base media item.

Abstract: An end user can sample a radio or television broadcast, generate a user representation of the broadcast sample, and send the user representation to a comparison system, which also receives known representations of content broadcast by multiple different stations. The known representations are stored in a continuous fashion, and represent actually broadcast content. The comparison system identifies the source of the broadcast sample by comparing the user representation to the known representations associated with each of the different stations using a bit count method, such as the Hamming distance. By comparing two representations of content that was actually broadcast, a broadcast source can be identified without requiring the use of watermarks, timestamps, or a database of discreet content items.

Abstract: Small changes in a broadcast version of a base media item can be identified by performing a multi-level comparison of digital fingerprints. A fingerprint of a base media item is compared to a fingerprint of a media broadcast to determine whether a media item embedded in a broadcast is likely, to a first level of certainty, to be the base media item. A second, more stringent, match between the fingerprint of the base media item and loosely matched items can be used to identify potentially-altered versions of the base media item. Potentially-altered versions can be compared against each other, and resulting matches are flagged as altered base media items, which can be fingerprinted and tested against broadcast fingerprints in the same manner as the base media item.

Abstract: An end user can sample a radio or television broadcast, generate a user representation of the broadcast sample, and send the user representation to a comparison system, which also receives known representations of content broadcast by multiple different stations. The known representations are stored in a continuous fashion, and represent actually broadcast content. The comparison system identifies the source of the broadcast sample by comparing the user representation to the known representations associated with each of the different stations. By comparing two representations of content that was actually broadcast, a broadcast source can be identified without requiring the use of watermarks, timestamps, or a database of discreet content items.

Abstract: An end user can sample a radio or television broadcast, generate a user representation of the broadcast sample, and send the user representation to a comparison system, which also receives known representations of content broadcast by multiple different stations. The known representations are stored in a continuous fashion, and represent actually broadcast content. The comparison system identifies the source of the broadcast sample by comparing the user representation to the known representations associated with each of the different stations. By comparing two representations of content that was actually broadcast, a broadcast source can be identified without requiring the use of watermarks, timestamps, or a database of discreet content items.

Abstract: An end user can sample a radio or television broadcast, generate a user representation of the broadcast sample, and send the user representation to a comparison system, which also receives known representations of content broadcast by multiple different stations. The known representations are stored in a continuous fashion, and represent actually broadcast content. The comparison system identifies the source of the broadcast sample by comparing the user representation to the known representations associated with each of the different stations. By comparing two representations of content that was actually broadcast, a broadcast source can be identified without requiring the use of watermarks, timestamps, or a database of discreet content items.

Abstract: A method includes receiving an audio fingerprint from a listening device. The method also includes, in response to determining that a portion of a stored audio fingerprint substantially matches a portion of the received audio fingerprint, identifying a longest unordered match between the received audio fingerprint and the stored audio fingerprint that satisfies a similarity threshold. The method further includes, in response to determining that the identified longest unordered match satisfies a length criterion, detecting a match between the received audio fingerprint and the stored audio fingerprint.

Abstract: An end user can sample a radio or television broadcast, generate a user representation of the broadcast sample, and send the user representation to a comparison system, which also receives known representations of content broadcast by multiple different stations. The known representations are stored in a continuous fashion, and represent actually broadcast content. The comparison system identifies the source of the broadcast sample by comparing the user representation to the known representations associated with each of the different stations. By comparing two representations of content that was actually broadcast, a broadcast source can be identified without requiring the use of watermarks, timestamps, or a database of discreet content items.

Abstract: An end user can sample a radio or television broadcast, generate a user representation of the broadcast sample, and send the user representation to a comparison system, which also receives known representations of content broadcast by multiple different stations. The known representations are stored in a continuous fashion, and represent actually broadcast content. The comparison system identifies the source of the broadcast sample by comparing the user representation to the known representations associated with each of the different stations. By comparing two representations of content that was actually broadcast, a broadcast source can be identified without requiring the use of watermarks, timestamps, or a database of discreet content items.