Abstract: A skip behavior analyzer is part of a media delivery system that allows for unbiased A/B testing of a plurality of versions of a song. The media delivery system stores a plurality of versions of a song and randomly selects, for each requesting device, a version of the song to associate with that device. Each time the device requests the song, thereafter, the media delivery system will provide the same version of the song for consistency. The media delivery system then gathers song play and skip information, calculates the differences in distribution of the skip behavior, and provides the skip information to allow a music composer to better determine which version of a song is more popular and why that is so.

Abstract: A system is provided for streaming media content in a vehicle. The system includes a personal media streaming appliance system configured to connect to a media delivery system and receive media content from the media delivery system at least via a cellular network. The personal media streaming appliance system operates to transmit a media signal representative to the received media content to a vehicle media playback system so that the vehicle media playback system operates to play the media content in the vehicle. Various types of rotations of a knob part of the personal media streaming applicant system result in different media playback actions.

Abstract: Term masking is performed by generating a time-alignment value for a plurality of identifiable units of sound in vocal audio content contained in a mixed audio track, force-aligning each of the plurality of identifiable units of sound to the vocal audio content based on the time-alignment value, thereby generating a plurality of force-aligned identifiable units of sound, identifying from the plurality of force-aligned identifiable units of sound a force-aligned identifiable unit of sound to be muddled, and audio muddling the force-aligned identifiable unit of sound to be muddled.

Abstract: An example system for playing media content with a media playback device in a vehicle can be programmed to obtain a sound measurement indicative of a sound level associated with playback of the media content by the media playback device in the vehicle. The example system also can determine a deviation in an expected sound level based upon the sound measurement. Finally, the system can modify playback of the media content by the media playback device (110) based upon the deviation.

Abstract: Methods, systems and computer program products are provided for identifying an audio stem. Audio stems (t1, . . . , tN) are stored on a stem database and songs (S1, . . . , SP) made with at least a subset of the plurality of the audio stems (t1, . . . , tN) are stored on a song database. At least partially composed song (S*) having a predetermined number of pre-selected stems (k) are received. In turn, a probability vector (or relevance value or ranking) is produced for each stem (t1, . . . , tN) to be complementary to the at least partially composed song (S*).

Abstract: In accordance with an embodiment, described herein is a system and method for use of cyclic play queues in a media content environment. A cyclic list data structure that can be initially populated with a list of media content items to be played at a media device, exposes a cyclic list of sequences of media content items, and supports operations to modify portions of the cyclic list to provide a cyclic play queue of media content items. When changes are made to an underlying play queue or context, the system performs a three-way merge of sequences of media content items within the cyclic list, to provide a modified play queue, for example with the left sequence being an updated playlist, and the right sequence being a patch window that reflects a user's changes to the play queue.

Abstract: A media-playback device acquires a heart rate, selects a song with a first tempo, and initiates playback of the song. The song meets a set of qualification criteria and the first tempo is based on the heart rate, such as being equal to or less than the heart rate. The media-playback device also initiates playback of a binaural beat at a first frequency. Over a period of time, the binaural beat's first frequency is changed to a second frequency. Over the period of time, the first tempo can also be changed to a second tempo, where the second tempo is slower than the first tempo.

Abstract: An electronic device associated with a media-providing service obtains listening history for a media item. The listening history includes retention information that indicates a number of listeners who listened to the respective portion of the media item. Using the retention information, the electronic device generates a retention graph that represents the number of listeners who listened to corresponding portions of the media item as a function of time. The electronic device detects an extremum in the retention graph. The extremum corresponds to a reduction in the number of listeners who listened to the corresponding portions of the media item. The electronic device determines whether the extremum meets predefined criteria, and in accordance with the determination that the extremum meets the predefined criteria, the electronic device stores an indication that the portions of the media item corresponding to the extremum include sub-content embedded in the media item.

Abstract: A system implements a dynamic correlated topic model (DCTM) to model an evolution of topic popularity, topic representation, and topic correlation within a set of documents, or other dataset, that spans a period of time. For example, the DCTM receives the set of documents and a quantity of topics for modeling. The DCTM processes the set by analyzing words of the documents, identifying word clusters representing the topics, and computing, for each topic, various distributions using continuous processes to capture a popularity, representation, and correlation with other topics across the period of time. In other examples, the dataset are user listening sessions comprised of media content items. Media content metadata (e.g., artist or genre) of the media content items, similar to words of a document, can be analyzed and clustered to represent topics for modeling by the DCTM.

Abstract: A method for communicating a playback order for a plurality of media content items to a user device operating in an online mode, the method performed at a server system and comprising receiving an indication that the user device will enter an offline mode, generating a playback order for the plurality of media content items, and transmitting the generated playback order to the user device before the user device enters the offline mode.

Abstract: A reinforcement learning ranker can take into account previously-recommended media content items to produce a ranked list of media content items to recommend next. The ranker finds a policy that gives the probability of sampling a media content item given a state. The policy is learned such that it maximizes a reward. A reward function associated with the media content item can be defined with respect to whether the user finds the media content item relevant (likelihood that the user will like the media content item) and a diversity score of the media content item.

Abstract: In accordance with an embodiment, described herein is a system and method for client-initiated playlist shuffle in a media content environment. A shuffle logic is configured to provide a shuffle order for a plurality of media content items, including associating each media content item with a placement interval within which the media content item can be placed, and a weight that determines the average position of the placement interval; associating each media content item with a random value that indicates a random offset or position within its placement interval; calculating an ordering score for each media content item based on its weight plus its random offset into its placement interval; collecting indications for the plurality of media content item that reflect their ordering scores; and placing the plurality of media content items into the shuffle order, for subsequent playback by a media device.

Abstract: A system that is distinct from a remote server and distinct from a client device receives, over a first communications channel, a first data stream for a first media item. The system receives, over a second communications channel, from an application at the client device, a second data stream for audio data that includes vocals provided by a user as the first media item plays. The system measures a latency of the second communications channel and overlays, with the first media item, the vocals provided by the user as the first media item plays to generate a composite data stream. The overlaying comprises offsetting the first data stream from the second data stream in accordance with the measured latency of the second communications channel and combining the first and second data streams in accordance with the offset of the data streams.

Abstract: Systems, devices, apparatuses, components, methods, and techniques for repetitive-motion activity enhancement based upon media content selection are provided. An example media-playback device for enhancement of a repetitive-motion activity includes a media-output device that plays media content items, a plurality of media content selection engines, and a repetitive-activity enhancement mode selection engine. The plurality of media content selection engines includes a cadence-based media content selection engine and an enhancement program engine. The cadence-based media content selection engine is configured to select media content items based on a cadence associated with the repetitive-motion activity. The enhancement program engine is configured to select a media content items according to an enhancement program for the repetitive-motion activity.

Abstract: Methods, systems, and computer programs for generating a playlist of media content items for a group of users. Media content items listened to by the selected users are compared to an average user taste profile to select media content items for playback to the group of users.

Abstract: Affinity scores are computed for a plurality of user accounts, each affinity score quantifies an affinity of a user account to a content creator of one or more digital objects hosted in a content hosting platform. Each affinity score is computed by collecting interaction data for the user account corresponding to the content creator, normalizing the collected interaction data using a total activity data of the user account on the content hosting platform and attribute data associated with the content creator, and generating the affinity score using the normalized interaction data.

Abstract: A server has a pool data store that stores ambient sound recordings for matching. A match engine finds matches between ambient sound recordings from devices in the pool data store. The matching ambient sound recordings and their respective devices are then analyzed to determine which device is a source device that provides credentials and which device is a target device that receives credentials. The server then obtains or generates credentials associated with the source device and provides the credentials to the target device. The target device accesses content or services of an account using the credentials.

Abstract: A call to action processor receives an entity datapoint containing data related to an entity, a campaign objective datapoint containing data associated with a campaign objective, at least one definite script element based on the campaign objective, and entity metadata containing data associated with the entity. The call to action further performs generating at least one variable script element based on the entity metadata, presenting to a device the at least one definite script element the at least one variable script element.