Some embodiments of the present disclosure relate to systems, devices, and methods for making recommendations to users for, individually or together, goods, services, and information/media (e.g., audio, video, publications), as well as verifying the veracity of data/information, based upon an emotional impact of such goods/services and/or media/information on the user, other users, and/or other individuals, as well some embodiments directed to systems, devices, and methods for treating one or more brain functions, including neurological conditions and episodes associated therewith by determining (and optionally providing) media (e.g., audio, but in some embodiments, any of audio, textual information, and video), which may be referred to as optimal medical media (“OMM”).

Some embodiments of the present disclosure relate to systems, devices, and methods for making recommendations to users for, individually or together, goods, services, and information/media (e.g., audio, video, publications), as well as verifying the veracity of data/information, based upon an emotional impact of such goods/services and/or media/information on the user, other users, and/or other individuals, as well some embodiments directed to systems, devices, and methods for treating one or more brain functions, including neurological conditions and episodes associated therewith by determining (and optionally providing) media (e.g., audio, but in some embodiments, any of audio, textual information, and video), which may be referred to as optimal medical media (“OMM”).

Methods, apparatus, systems and articles of manufacture to credit unidentified media are disclosed. Disclosed example apparatus include a database updater to store a first group of signatures representative of unidentified media in a database, the first group of signatures obtained from a first media meter to monitor a first media presentation device, the first group of signatures associated with a first media exposure category based on media source information reported by the first media meter. Disclosed example apparatus also include a media comparator to compare a second group of signatures with the first group of signatures, the second group of signatures obtained from a second media meter to monitor a second media presentation device. Disclosed example apparatus further include a reporter to credit media exposure represented by the second group of signatures to the first media exposure category when the second group of signatures matches the first group of signatures.

Methods, apparatus, systems and articles of manufacture to credit unidentified media are disclosed. Disclosed example apparatus include a database updater to store a first group of signatures representative of unidentified media in a database, the first group of signatures obtained from a first media meter to monitor a first media presentation device, the first group of signatures associated with a first media exposure category based on media source information reported by the first media meter. Disclosed example apparatus also include a media comparator to compare a second group of signatures with the first group of signatures, the second group of signatures obtained from a second media meter to monitor a second media presentation device. Disclosed example apparatus further include a reporter to credit media exposure represented by the second group of signatures to the first media exposure category when the second group of signatures matches the first group of signatures.

Systems and methods for delivering exercise content to a user of an exercise apparatus include a database storing exercise content, data associated with a content provider and data associated with an application provider, and a platform server operable to facilitate delivery of the exercise content to the exercise apparatus. The platform server delivers for display on the exercise apparatus archived exercise classes for selection by the user, receives from the exercise apparatus a selection, transmits data representing content of the selected archived exercise class, receives performance data from the exercise apparatus based on activity by the user, and generates archived performance data representing archived user performance parameters for a plurality of other users over at least the portion of the selected archived exercise class. Data is synchronized and updated for display by the exercise apparatus to simulate the user competing with at least some of the other users.

The present disclosure relates to a method of providing media to a user based on analysis of an image. The method comprises analysing the image to obtain image information about what is depicted therein. The method also comprises, based on said obtained image information, selecting a first plurality of media items comprising audio, from a media database, said media items of the first plurality being associated with that which is depicted in the image according to the image information. The method also comprises filtering the first plurality of media items based on metadata associated with the user to obtain a plurality of seed media items. The method also comprises providing at least one media item from the media database to the user based on the obtained seed media items.

The present disclosure relates to a method of providing media to a user based on analysis of an image. The method comprises analysing the image to obtain image information about what is depicted therein. The method also comprises, based on said obtained image information, selecting a first plurality of media items comprising audio, from a media database, said media items of the first plurality being associated with that which is depicted in the image according to the image information. The method also comprises filtering the first plurality of media items based on metadata associated with the user to obtain a plurality of seed media items. The method also comprises providing at least one media item from the media database to the user based on the obtained seed media items.

Systems and methods are directed to auto-adjusting play time of slides based on content intelligence. The system accesses media comprising a plurality of media items, wherein a media item of the plurality of media items comprises a first content type. The system performs machine analysis associated with the first content type. Based on the machine analysis, the system determines a first display time for the first content type and derives a total display time for the media item based on the first display time. If the media item includes a second content type, then the system performs machine analysis associated with the second content type and determines a second display time for the second content type. The total display time now comprises an aggregation of the first and second display times. The system can cause a machine action based on the total display time.

Techniques are disclosed for automatic scene detection and character extraction. In one example, audiovisual content with video frames, an audio recording, and timing information is received. A score, based on the frame's visual characteristics, is determined for a first frame and subsequent frames. The first frame's score and subsequent frame's scores are compared to determine if the difference between the scores is above a threshold. When the difference in scores is above a threshold, the subsequent frame is classified as a new scene. The audiovisual content is segmented into scenes and textual characters are identified in at least one frame from each scene. The characters are stored and indexed in a searchable database with the timing information for the scene where the characters were identified. The audio recording is transcribed and the transcribed words are stored and indexed in the searchable database with timing information.

Techniques are disclosed for automatic scene detection and character extraction. In one example, audiovisual content with video frames, an audio recording, and timing information is received. A score, based on the frame's visual characteristics, is determined for a first frame and subsequent frames. The first frame's score and subsequent frame's scores are compared to determine if the difference between the scores is above a threshold. When the difference in scores is above a threshold, the subsequent frame is classified as a new scene. The audiovisual content is segmented into scenes and textual characters are identified in at least one frame from each scene. The characters are stored and indexed in a searchable database with the timing information for the scene where the characters were identified. The audio recording is transcribed and the transcribed words are stored and indexed in the searchable database with timing information.