Abstract: Methods, apparatus, and systems are disclosed for synchronizing streaming media content. An example apparatus includes a storage device, and a processor to execute instructions to identify a first source streaming broadcast media to a first computing device based on an audio fingerprint of audio associated with the broadcast media, identify sources broadcasting the broadcast media streaming to the first computing device, the sources available to a second computing device including the processor, select a second source of the identified sources for streaming the broadcast media to the second computing device, the second source different than the first source, detect termination of the streaming of the broadcast media on the first computing device, the termination corresponding to a termination time of the broadcast media, and automatically start, by using the selected second source, streaming of the broadcast media to the second computing device at the termination time.

Abstract: Example methods and systems for inserting information into playing content are described. In some example embodiments, the methods and systems may identify a break in content playing via a playback device, select an information segment representative of information received by the playback device to present during the identified break, and insert the information segment into the content playing via the playback device upon an occurrence of the identified break.

Abstract: Methods and apparatus for harmonic source enhancement are disclosed herein. An example apparatus includes an interface to receive a media signal. The example apparatus also includes a harmonic source enhancer to determine a magnitude spectrogram of audio corresponding to the media signal; generate a time-frequency mask based on the magnitude spectrogram; and apply the time-frequency mask to the magnitude spectrogram to enhance a harmonic source of the media signal.

Abstract: Methods and systems for modification of electronic system operation based on acoustic ambience classification are presented. In an example method, at least one audio signal present in a physical environment of a user is detected. The at least one audio signal is analyzed to extract at least one audio feature from the audio signal. The audio signal is classified based on the audio feature to produce at least one classification of the audio signal. Operation of an electronic system interacting with the user in the physical environment is modified based on the classification of the audio signal.

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: A computing system determines accuracy of sport-related information extracted from a time sequence of digital video frames that represent a sport event, the extracted sport-related information including an attribute that changes over the time sequence. The computing system (a) detects, based on the extracted sport-related information, a pattern of change of the attribute over the time sequence and (b) makes a determination of whether the detected pattern is an expected pattern of change associated with the sport event. If the determination is that the detected pattern is the expected pattern, then, responsive to making the determination, the computing system takes a first action that corresponds to the sport-related information being accurate. Whereas, if the determination is that the detected pattern is not the expected pattern, then, responsive to making the determination, the computing system takes a second action that corresponds to the sport-related information being inaccurate.

Abstract: Apparatus, systems, articles of manufacture, and methods for volume adjustment are disclosed herein. An example method includes collecting data corresponding to a volume of an audio signal as the audio signal is output through a device, when an average volume of the audio signal does not satisfy a volume threshold for a specified timespan, determining a difference between the average volume and a desired volume, and applying a gain to the audio signal to adjust the volume of the audio signal to the desired volume, the gain determined based on the difference between the average volume and the desired volume.

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, sending, by the media playback device to a server, a preview request, the preview request identifying a second channel that is different from the first channel; (ii) receiving, by the media playback device from the server, a response to the preview request, the response including identifying information corresponding to content being provided on the second channel; and (iii) while the media playback device is playing back the content received on the first channel, providing, by the media playback device for display, at least a portion of the identifying information corresponding to content being provided on the second channel.

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: A computing system automatically extracting, from a digital video frame, scoreboard information including a first team name, a second team name, a first score, and a second score. The computing system (a) detects, within the digital video frame, a plurality of frame regions based on each detected frame region depicting text; (b) selects, from the detected frame regions, a set of frame regions based on the frame regions of the selected set cooperatively having a geometric arrangement that corresponds with a candidate geometric arrangement of the scoreboard information; (c) recognizes characters respectively within each of the frame regions of the selected set of frame regions; (d) based at least on the recognized characters in the frame regions of the selected set, detects the scoreboard information; and (e) records the detected scoreboard information.

Abstract: Methods, apparatus, systems, and articles of manufacture to fingerprint an audio signal. An example apparatus disclosed herein includes an audio segmenter to divide an audio signal into a plurality of audio segments, a bin normalizer to normalize the second audio segment to thereby create a first normalized audio segment, a subfingerprint generator to generate a first subfingerprint from the first normalized audio segment, the first subfingerprint including a first portion corresponding to a location of an energy extremum in the normalized second audio segment, a portion strength evaluator to determine a likelihood of the first portion to change, and a portion replacer to, in response to determining the likelihood does not satisfy a threshold, replace the first portion with a second portion to thereby generate a second subfingerprint.

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: A computing system engages in digital image processing of received video frames to generate sport data that indicates a score and/or a time associated with a sport event. The digital image processing includes: (i) identifying a first frame region of the video frames based on the first frame region depicting a scoreboard; (ii) executing a first procedure that analyzes the identified first frame region to detect, within the identified first frame region, second frame region(s) based on the second frame region(s) depicting text of the scoreboard; (iii) in response to detecting the second frame region(s), executing a second procedure to recognize the text in at least one of the second frame region(s); and (iv) based at least on the recognizing of the text, generating the sport data. In response to completing the digital image processing, the computing system then carries out an action based on the generated sport data.

Abstract: A computing system automatically detects, within a digital video frame, a video frame region that depicts a textual expression of a scoreboard. The computing system (a) engages in an edge-detection process to detect edges of at least scoreboard image elements depicted by the digital video frame, with at least some of these edges being of the textual expression and defining alphanumeric shapes; (b) applies pattern-recognition to identify the alphanumeric shapes; (c) establishes a plurality of minimum bounding rectangles each bounding a respective one of the identified alphanumeric shapes; (d) establishes, based on at least two of the minimum bounding rectangles, a composite shape that encompasses the identified alphanumeric shapes that were bounded by the at least two minimum bounding rectangles; and (e) based on the composite shape occupying a particular region, deems the particular region to be the video frame region that depicts the textual expression.

Abstract: An example method may include receiving, at a computing device, a digital image associated with a particular media content program, the digital image containing one or more faces of particular people associated with the particular media content program. A computer-implemented automated face recognition program may be applied to the digital image to recognize, based on at least one feature vector from a prior-determined set of feature vectors, one or more of the particular people in the digital image, together with respective geometric coordinates for each of the one or more detected faces. At least a subset of the prior-determined set of feature vectors may be associated with a respective one of the particular people. The digital image together may be stored in non-transitory computer-readable memory, together with information assigning respective identities of the recognized particular people, and associating with each respective assigned identity geometric coordinates in the digital image.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for playback using pre-processed profile information and personalization. Example apparatus disclosed herein include a synchronizer to, in response to receiving a media signal to be played on a playback device, access an equalization (EQ) profile corresponding to the media signal; an EQ personalization manager to generate a personalized EQ setting; and an EQ adjustment implementor to modify playback of the media signal on the playback device based on a blended equalization generated based on the EQ profile and the personalized EQ setting.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for dynamic volume adjustment via audio classification.

Abstract: Example systems and methods of selection of video frames using a machine learning (ML) predictor program are disclosed. The ML predictor program may generate predicted cropping boundaries for any given input image. Training raw images associated with respective sets of training master images indicative of cropping characteristics for the training raw image may be input to the ML predictor, and the ML predictor program trained to predict cropping boundaries for raw image based on expected cropping boundaries associated training master images. At runtime, the trained ML predictor program may be applied to a sequence of video image frames to determine for each respective video image frame a respective score corresponding to a highest statistical confidence associated with one or more subsets of cropping boundaries predicted for the respective video image frame. Information indicative of the respective video image frame having the highest score may be stored or recorded.

Abstract: Methods and systems for automated video segmentation are disclosed. A sequence of video frames having video segments of contextually-related sub-sequences may be received. Each frame may be labeled according to segment and segment class. A video graph may be constructed in which each node corresponds to a different frame, and each edge connects a different pair of nodes, and is associated with a time between video frames and a similarity metric of the connected frames. An artificial neural network (ANN) may be trained to predict both labels for the nodes and clusters of the nodes corresponding to predicted membership among the segments, using the video graph as input to the ANN, and ground-truth clusters of ground-truth labeled nodes. The ANN may be further trained to predict segment classes of the predicted clusters, using the segment classes as ground truths. The trained ANN may be configured for application runtime video sequences.

Abstract: Techniques of providing motion video content along with audio content are disclosed. In some example embodiments, a computer-implemented system is configured to perform operations comprising: receiving primary audio content; determining that at least one reference audio content satisfies a predetermined similarity threshold based on a comparison of the primary audio content with the at least one reference audio content; for each one of the at least one reference audio content, identifying motion video content based on the motion video content being stored in association with the one of the at least one reference audio content and not stored in association with the primary audio content; and causing the identified motion video content to be displayed on a device concurrently with a presentation of the primary audio content on the device.