Abstract: Techniques of content unification are disclosed. In some example embodiments, a computer-implemented method comprises: determining clusters based a comparison of a plurality of audio content using a first matching criteria, each cluster of the plurality of clusters comprising at least two audio content from the plurality of audio content; for each cluster of the plurality of clusters, determining a representative audio content for the cluster from the at least two audio content of the cluster; loading the corresponding representative audio content of each cluster into an index; matching the query audio content to one of the representative audio contents using a first matching criteria; determining the corresponding cluster of the matched representative audio content; and identifying a match between the query audio content and at least one of the audio content of the cluster of the matched representative audio content based on a comparison using a second matching criteria.

Abstract: Systems and methods are provided for filtering at least one media content catalog based on criteria for a station library to generate a first list of candidate tracks for the station library, combining a similarity score and a popularity score for each track of the first list of candidate tracks to generate a total score for each track of the first list of candidate tracks, generating a list of top ranked tracks for the first genre, and returning the list of top ranked tracks of the first genre as part of the station library.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed methods and apparatus for audio equalization based on variant selection. An example apparatus includes a processor to obtain training data, the training data including a plurality of reference audio signals each associated with a variant of music and organize the training data into a plurality of entries based on the plurality of reference audio signals, a training model executor to execute a neural network model using the training data, and a model trainer to train the neural network model by updating at least one weight corresponding to one of the entries in the training data when the neural network model does not satisfy a training threshold.

Abstract: Methods, apparatus and systems are disclosed to generate light control information. An example apparatus comprises a beat tracking network to determine a length of time between a first media onset and a second media onset, a light drive waveform generator to compare the length of time to a time threshold, the time threshold corresponding to a desired time between consecutive light pulses, when the time threshold is not satisfied, increase the length of time, the increased length of time corresponding to light pulse spacing, and generate light control information based on the light pulse spacing, the light control information to cause the consecutive light pulses, and an effect engine to generate intensity information based on a first amplitude of the first media onset and a second amplitude of the second media onset, an amplitude of the consecutive light pulses corresponding to the intensity information.

Abstract: Example systems and methods for automated cover song identification are disclosed. An example apparatus includes memory, and one or more processors to execute instructions to identify query audio from a content source based on a search query using rights metadata associated with the query audio, execute a constant Q transform on query time slices of the query audio, binarize the constant Q transformed query time slices, execute a two-dimensional Fourier transform on query time windows within the binarized and constant Q transformed query time slices to generate two-dimensional Fourier transforms of the query time windows, generate a query data structure based on a sequential order of the two-dimensional Fourier transforms, select a subset including reference audio of a reference database based on the rights metadata, and identify the query audio as a cover rendition of the reference audio based on a comparison between the query and reference data structures.

Abstract: In one aspect, an example method to be performed by a vehicle-based media system includes (a) receiving audio content; (b) causing one or more speakers to output the received audio content; (c) using a microphone of the vehicle-based media system to capture the output audio content; (d) identifying reference audio content that has at least a threshold extent of similarity with the captured audio content; (e) identifying a geographic location associated with the identified reference audio content; and (f) based at least on the identified geographic location associated with the identified reference audio content, outputting, via the user interface of the vehicle-based media system, a prompt to navigate to the identified geographic location.

Abstract: In one aspect, an example method includes (i) retrieving, from a text index, closed captioning repetition data for a segment of a sequence of media content; (ii) generating features using the closed captioning repetition data; (iii) providing the features as input to a classification model, wherein the classification model is configured to output classification data indicative of a likelihood of the features being characteristic of a program segment; (iv) obtaining the classification data output by the classification model; (v) determining a prediction of whether the segment is a program segment using the classification data; and (vi) storing the prediction for the segment in a database.

Abstract: Apparatus, methods, and systems that operate to provide interactive streaming content identification and processing are disclosed. An example apparatus includes a classifier to determine an audio characteristic value representative of an audio characteristic in audio; a transition detector to detect a transition between a first category and a second category by comparing the audio characteristic value to a threshold value among a set of threshold values, the set of threshold values corresponding to the first category and the second category; and a context manager to control a device to switch from a first fingerprinting algorithm to a second fingerprinting algorithm different than the first fingerprinting algorithm, responsive to the detected transition between the first category and the second category.

Abstract: In an example implementation, a method is described. The implementation accesses a plurality of media clips including a first video clip and a second video clip, matches a first fingerprint of the first video clip with a second fingerprint of the second video clip. The implementation also matches a first event subject of the first video clip with a second event subject of the second video clip, and determines an overlap of the first video clip with the second video clip based at least in part on the match of the first fingerprint with the second fingerprint and the match of the first event subject with the second event subject. The implementation also merges the first video clip and the second video clip into a group of overlapping video clips based on the overlap, and synthesizes the group into a video presentation.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for a broadcast profiling system. An example method includes comparing a preference included in a user profile with a portion of a content station profile to determine whether the preference satisfies a threshold difference from the portion of the content station profile, the content station profile including (1) a first characteristic of first broadcast data associated with a first time context and a first count associated with first identifying information and (2) a second characteristic of second broadcast data associated with a second time context and a second count associated with second identifying information; in response to the threshold difference being satisfied, generating a station recommendation for a user associated with the user profile; and transmitting an instruction associated with the user, the instruction including the station recommendation, the instruction configured to cause a radio pre-set to be adjusted.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to identify media that has been pitch shifted, time shifted, and/or resampled. An example method includes: generating, by executing an instruction with a processor, a fingerprint from an audio signal; transmitting the fingerprint and adjusting instructions to a central facility to facilitate a query, the adjusting instructions identifying at least one of a pitch shift or a time shift; and receiving a response including an identifier for the audio signal and information corresponding to how the audio signal was adjusted; storing information indicative of the identifier and the information into a database.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to identify media. An example method includes: in response to a query, generating an adjusted sample media fingerprint by applying an adjustment to a sample media fingerprint; comparing the adjusted sample media fingerprint to a reference media fingerprint; and in response to the adjusted sample media fingerprint matching the reference media fingerprint, transmitting information associated with the reference media fingerprint and the adjustment.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for audio equalization based on variant selection. An example apparatus to generate equalization adjustments for an audio signal includes an input feature set generator to generate an equalization input feature set by generating a data structure corresponding to a user input, the data structure including a number of entries identifying a selected variant of music and including the data structure in the equalization input feature set, and a model executor to, in response to obtaining the equalization input feature set, adjust at least one weight of a neural network model to generate the equalization adjustments for the audio signal.

Abstract: In one aspect, an example method to be performed by a vehicle-based media system includes (a) receiving audio content; (b) causing one or more speakers to output the received audio content; (c) using a microphone of the vehicle-based media system to capture the output audio content; (d) identifying reference audio content that has at least a threshold extent of similarity with the captured audio content; (e) identifying visual content based at least on the identified reference audio content; and (f) outputting, via a user interface of the vehicle-based media system, the identified visual content.

Abstract: 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.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to identify media. An example method includes: in response to a query, generating an adjusted sample media fingerprint by applying an adjustment to a sample media fingerprint; comparing the adjusted sample media fingerprint to a reference media fingerprint; and in response to the adjusted sample media fingerprint matching the reference media fingerprint, transmitting information associated with the reference media fingerprint and the adjustment.

Abstract: In one aspect, an example method to be performed by a computing device includes (a) determining that a ride-sharing session is active; (b) in response to determining the ride-sharing session is active, using a microphone of the computing device to capture audio content; (c) identifying reference audio content that has at least a threshold extent of similarity with the captured audio content; (d) determining that the ride-sharing session is inactive; and (e) outputting an indication of the identified reference audio content.

Abstract: In one aspect, a method includes receiving podcast content, generating a transcript of at least a portion of the podcast content, and parsing the podcast content to (i) identify audio segments within the podcast content, (ii) determine classifications for the audio segments, (iii) identify audio segment offsets, and (iv) identify sentence offsets. The method also includes based on the audio segments, the classifications, the audio segment offsets, and the sentence offsets, dividing the generated transcript into text sentences and, from among the text sentences of the divided transcript, selecting a group of text sentences for use in generating an audio summary of the podcast content. The method also includes based on timestamps at which the group of text sentences begin in the podcast content, combining portions of audio in the podcast content that correspond to the group of text sentences to generate an audio file representing the audio summary.

Abstract: Methods, apparatus, systems and articles of manufacture of logo recognition in images and videos are disclosed. An example method to detect a specific brand in images and video streams comprises accepting luminance images at a scale in an x direction Sx and a different scale in a y direction Sy in a neural network, and training the neural network with a set of training images for detected features associated with a specific brand.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for efficient media indexing. An example method disclosed herein includes selecting a first hash seed value based on a first entropy value calculated for a first bucket distribution resulting from use of the first hash seed value to store data in a first hash table, selecting a second hash seed value to be used in combination with the first hash seed value based on a second entropy value calculated on a second bucket distribution resulting from use of the first hash seed value in combination with the second hash seed value, and storing data in the first hash table based on the first hash seed value and a second hash table based on the second hash seed value.