Abstract: Systems, methods, and non-transitory computer-readable media can store fingerprint data corresponding to one or more content items in an index data structure, the index data structure comprising a set of bins, wherein at least one first bin references a list of fingerprinted frames, and wherein at least one fingerprinted frame in the list corresponds to a first content item. A determination is made that one or more fingerprinted frames corresponding to a second content item are to be added to the index data structure. At least one of the fingerprinted frames corresponding to the second content item are added to the list of fingerprinted frames that is referenced by the first bin.

Abstract: Systems, methods, and non-transitory computer-readable media can generate at least one fingerprint based on a set of frames corresponding to a test content item, generate a set of distorted fingerprints using at least a portion of the fingerprint, and determine one or more reference content items using the set of distorted fingerprints, wherein the test content item is evaluated against at least one reference content item to identify matching content.

Abstract: An audio identification system generates audio fingerprints and indexes associated with the audio fingerprints based on discrete and overlapping frames within a sample of an audio signal. The system applies a time-to-frequency domain transform to a time-sequence of frames, which may be filtered. The audio identification system then applies a time-variant transformation (e.g., a Discrete Cosine Transform) to the transformed frames and generates an audio fingerprint and index by selecting sets of coefficients of the time-variant transformation. The system selects coefficients that are less sensitive to possible noise and/or distortions in the underlying signal, such as low-frequency coefficients. The time-variant transformation provides sufficient sampling among the indexes by incorporating the phase information of the frames into the indexes. The system stores the audio fingerprint and other identifying information by index for efficient retrieval and matching of the retrieved fingerprints.

Abstract: An audio identification system accounts for an audio signal's complexity when generating a test audio fingerprint for identification of the audio signal. In particular, the audio identification system determines a complexity of an audio signal to be fingerprinted. For example, the audio signal's complexity may be determined by performance of an autocorrelation on the audio signal. Based on the determined complexity, the audio identification system determines a length of a sample of the audio signal used to generate a test audio fingerprint. A sample having the length is then obtained and used to generate a test audio fingerprint for the audio signal. The test audio fingerprint may be compared to a set of reference audio fingerprints to identify the audio signal.

Abstract: The present disclosure provides identification and continuous monitoring of content, such as broadcast content, in real time, using a hierarchical, distributed approach to content identification. Identification, synchronization and verification are provided. Identification may be performed by an identification server using a reference database of fingerprints. The same or another computing device may be used perform synchronization, such that at least some portion of each fingerprint generated by client devices that form a verification group are synchronized for verification. Verification used to determine whether a client device continues to receive the same content identified during identification compares at least a portion of each fingerprint generated by each client device of a verification group. If a mismatch occurs, identification may be repeated to identify the new content being received by a client device.

Abstract: Systems, methods, and non-transitory computer-readable media can generate at least one first fingerprint based at least in part on one or more frames corresponding to a test content item. At least one second fingerprint is generated based at least in part on the one or more frames corresponding to the test content item. One or more reference content items are determined based on the at least one first fingerprint. The test content item is evaluated against at least one reference content item to identify matching content based on the at least one second fingerprint.

Abstract: An audio identification system determines whether a portion of a sample of an audio signal includes silence and generates a test audio fingerprint for the audio signal based on the presence of silence. In one embodiment, the audio identification system uses a value indicating silence for a portion of the test audio fingerprint corresponding to the portion of the audio signal that includes silence. When comparing the test audio fingerprint to reference audio fingerprints, the portion of the test audio fingerprint including the value indicating the presence of silence is not used. In another embodiment, the audio identification system replaces the portion including silence with additive audio and generates a test audio fingerprint for comparison based on the resulting modified sample.

Abstract: An audio identification system generates a probe audio fingerprint of an audio signal and determines amount of pitch shifting in the audio signal based on analysis of correlation between the probe audio fingerprint and a reference audio fingerprint. The audio identification system applies a time-to-frequency domain transform to frames of the audio signal and filters the transformed frames. The audio identification system applies a two-dimensional discrete cosine transform (DCT) to the filtered frames and generates the probe audio fingerprint from a selected number of DCT coefficients. The audio identification system calculates a DCT sign-only correlation between the probe audio fingerprint and the reference audio fingerprint, and the DCT sign-only correlation closely approximates the similarity between the audio characteristics of the probe audio fingerprint and those of the reference audio fingerprint.

Abstract: Systems, methods, and non-transitory computer-readable media can generate at least one first fingerprint based at least in part on one or more frames corresponding to a test content item. At least one second fingerprint is generated based at least in part on the one or more frames corresponding to the test content item. One or more reference content items are determined based on the at least one first fingerprint. The test content item is evaluated against at least one reference content item to identify matching content based on the at least one second fingerprint.

Abstract: An audio identification system generates a reference audio fingerprint associated with an event. The reference audio fingerprint is generated from samples of an audio signal associated with the event captured by multiple devices. To generate the reference audio fingerprint, fingerprints are generated from each sample, and the generated fingerprints are temporally aligned. Fingerprints associated a temporally overlapping portion of the audio signal are averaged, and the average value is associated with the temporally overlapping portion of the audio signal and included in the reference audio fingerprint. The reference audio fingerprint is stored along with identifying information, such as an event name, an event time, an event date, or other information describing the event associated with the audio signal from which the samples were captured.

Abstract: An audio identification system generates audio fingerprints and indexes associated with the audio fingerprints based on discrete and overlapping frames within a sample of an audio signal. The system applies a time-to-frequency domain transform to a time-sequence of frames, which may be filtered. The audio identification system then applies a time-variant transformation (e.g., a Discrete Cosine Transform) to the transformed frames and generates an audio fingerprint and index by selecting sets of coefficients of the time-variant transformation. The system selects coefficients that are less sensitive to possible noise and/or distortions in the underlying signal, such as low-frequency coefficients. The time-variant transformation provides sufficient sampling among the indexes by incorporating the phase information of the frames into the indexes. The system stores the audio fingerprint and other identifying information by index for efficient retrieval and matching of the retrieved fingerprints.

Abstract: Systems, methods, and non-transitory computer-readable media can generate at least one fingerprint based on a set of frames corresponding to a test content item, generate a set of distorted fingerprints using at least a portion of the fingerprint, and determine one or more reference content items using the set of distorted fingerprints, wherein the test content item is evaluated against at least one reference content item to identify matching content.

Abstract: Systems, methods, and non-transitory computer-readable media can store fingerprint data corresponding to one or more content items in an index data structure, the index data structure comprising a set of bins, wherein at least one first bin references a list of fingerprinted frames, and wherein at least one fingerprinted frame in the list corresponds to a first content item. A determination is made that one or more fingerprinted frames corresponding to a second content item are to be added to the index data structure. At least one of the fingerprinted frames corresponding to the second content item are added to the list of fingerprinted frames that is referenced by the first bin.

Abstract: Systems, methods, and non-transitory computer-readable media can obtain a test content item having a plurality of video frames. At least one video fingerprint is determined based on a set of video frames corresponding to the test content item. At least one reference content item is determined using at least a portion of the video fingerprint. At least one portion of the test content item that matches at least one portion of the reference content item is determined based at least in part on the video fingerprint of the test content item and one or more video fingerprints of the reference content item.

Abstract: Systems, methods, and non-transitory computer-readable media can obtain a test content item having a plurality of video frames. At least one video fingerprint is determined based on a set of video frames corresponding to the test content item. At least one reference content item is determined using at least a portion of the video fingerprint. At least one portion of the test content item that matches at least one portion of the reference content item is determined based at least in part on the video fingerprint of the test content item and one or more video fingerprints of the reference content item.

Abstract: An audio identification system generates audio fingerprints and indexes associated with the audio fingerprints based on discrete and overlapping frames within a sample of an audio signal. The system applies a time-to-frequency domain transform to a time-sequence of frames, which may be filtered. The audio identification system then applies a time-variant transformation (e.g., a Discrete Cosine Transform) to the transformed frames and generates an audio fingerprint and index by selecting sets of coefficients of the time-variant transformation. The system selects coefficients that are less sensitive to possible noise and/or distortions in the underlying signal, such as low-frequency coefficients. The time-variant transformation provides sufficient sampling among the indexes by incorporating the phase information of the frames into the indexes. The system stores the audio fingerprint and other identifying information by index for efficient retrieval and matching of the retrieved fingerprints.

Abstract: A commercial detection system generates a probe audio fingerprint of an audio signal associated with a media stream on a broadcast channel and determines whether the media stream has commercial content based on analysis of the probe audio fingerprint. The commercial detection system determines whether a same match between the probe audio fingerprint and a reference audio fingerprint is observed across multiple broadcast channels. Responsive to the number of same matches exceeding a predetermined threshold, the commercial detection system determines that the media stream has commercial content. The commercial detection system may also apply a trained feature analysis model to extracted acoustic features of the audio signal. The commercial detection system determines whether the media stream has commercial content based on a confidence score assigned to the probe audio fingerprint. The commercial detection system reduces false positive detection using program guide information of the media stream.

Abstract: An audio identification system accounts for an audio signal's complexity when generating a test audio fingerprint for identification of the audio signal. In particular, the audio identification system determines a complexity of an audio signal to be fingerprinted. For example, the audio signal's complexity may be determined by performance of an autocorrelation on the audio signal. Based on the determined complexity, the audio identification system determines a length of a sample of the audio signal used to generate a test audio fingerprint. A sample having the length is then obtained and used to generate a test audio fingerprint for the audio signal. The test audio fingerprint may be compared to a set of reference audio fingerprints to identify the audio signal.

Abstract: The present disclosure provides identification and continuous monitoring of content, such as broadcast content, in real time, using a hierarchical, distributed approach to content identification. Identification, synchronization and verification are provided. Identification may be performed by an identification server using a reference database of fingerprints. The same or another computing device may be used perform synchronization, such that at least some portion of each fingerprint generated by client devices that form a verification group are synchronized for verification. Verification used to determine whether a client device continues to receive the same content identified during identification compares at least a portion of each fingerprint generated by each client device of a verification group. If a mismatch occurs, identification may be repeated to identify the new content being received by a client device.

Abstract: Systems, methods, and non-transitory computer-readable media can determine that a publisher is providing a first live content stream for distribution through the social networking system, the first live content stream including copyrighted content. A determination is made that a broadcaster is providing a second live content stream for distribution through the social networking system. The first live content stream and the second live content stream are exposed to at least some users of the social networking system. While the first live content stream and the second live content stream are being distributed through the social networking system, a determination is made that at least some portions of the second live content stream match copyrighted content included in the first live content stream. At least one notification is provided to the broadcaster of the second live content stream, wherein the notification indicates a potential copyright violation by the broadcaster.