Abstract: An electronic device receives a first media content item and receives information indicating: a first insertion time within the first media content item; and a second media content item to be played at the first insertion time and/or one or more properties of the second media content item. The electronic device stores the first media content item. The electronic device provides the first media content item to the second electronic device, including queuing the second electronic device to playback, in sequence and without user intervention: the first media content item until the first insertion time; the second media content item at the first insertion time; and the first media content item resumed after playback of the second media content item is ceased.

Abstract: Systems and methods for snapping to seek positions in media content using seek guides are provided. Seek guides may be associated with a media content item. Each seek guide may have a position and a radius. When a user seeks to a reference position, a seek guide selector may select a seek guide to use in setting a new playback position. The seek guide selector may use a probabilistic distribution positioned based on the reference position to select a seek guide. Probabilities may be calculated for each seek guide using a cumulative distribution function, and a seek guide may be selected based on the calculated probabilities.

Abstract: A server system receives a request to generate a playlist. The playlist includes a sequence of media items. The server system receives a plurality of constraints that define disqualification criteria for excluding media items from a respective slot in the sequence of media items. The plurality of constraints for the respective slot in the sequence of media items includes at least one constraint that is based on already-populated slots in the sequence of media items. The server system generates the playlist by sequentially populating each respective slot in the sequence of media items, including selecting, for the respective slot, a respective media item that meets the plurality of constraints for the respective slot in the sequence of media items. The server system provides the playlist to a user of the media providing service.

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: Systems and methods for performing bias bounded sensitivity analysis of synthetic control models are provided. Bias bounds may be determined for a synthetic control model using data from the synthetic control model. If a difference between a synthetic control determined by the synthetic control model and an observed outcome are within the bias bounds, a causal effect determined using the synthetic control model may be untrustworthy. Graphical representations may be presented based, at least in part, on the observed outcome, the synthetic control, and the bias bounds.

Abstract: Systems and methods for automatically organizing narrated media content based on a media description file are provided. For example, a media description file may be received with narrated media content. The media description file may include information about the narrated media content, such as entitlement levels associations between narrated media content items. The narrated media content may be automatically labeled based on the media description file. A personalized user interface may be generated based on the labeled narrated media content and user subscription tiers.

Abstract: A method is performed at a server system associated with a media streaming service. The method includes providing, a first client device, playback of a first media content item; and receiving, from the first client device, a second media content item to be associated with the first media content item. The method includes, after receiving the second media content item from the first client device: providing, a second client device, a user interface that includes graphical representations of a plurality of media content items that have been uploaded by other users of the media streaming service as related to the first media content item; receiving, from the second client device, a user selection of a graphical representation of the second media content item; and in response, providing the second media content item concurrently with playback of the first media content item.

Abstract: A system and method for controlling access to an on-device machine learning model without the use of encryption is described herein. For example, a request is received from an application executing on a device of a user. The request is to download a machine learning model to the device that enables a feature of the application, and the request includes information associated with the user and/or the device. The information is used to create an obfuscation key, and a derivative model can be generated using a reference copy of the machine learning model and the obfuscation key. The derivative model and the obfuscation key are then sent to the application. When the obfuscation key is provided to the derivative model at runtime, values derived from the obfuscation key are provided as additional inputs that enable the derivative model to function properly.

Abstract: The various implementations described herein include methods and devices for speaker diarization. In one aspect, a method includes obtaining an audio recording and generating an embedding signal from the audio recording. The method further includes factoring the embedding signal to obtain a basis matrix and an activation matrix, including obtaining a sparse optimization of the embedding signal by minimizing a norm corresponding to the factored embedding signal. The method also includes generating a speaker log for the audio recording based on the sparse optimization of the embedding signal.

Abstract: Systems, methods, and devices for human-machine interfaces for improving machine understanding and fulfillment of utterance-based requests provided via the interfaces. Multiple candidate understandings from multiple stages of a natural language processing flow are preserved for arbitration and choosing by an arbitrator that applies arbitration rules to the plurality of candidates and chooses a single candidate for initiation of a corresponding service. In an embodiment, the arbitrator uses a media content taste profile to choose a candidate understanding for initiation of a corresponding service.

Abstract: A system, method and computer product for training a neural network system. The method comprises applying an audio signal to the neural network system, the audio signal including a vocal component and a non-vocal component. The method also comprises comparing an output of the neural network system to a target signal, and adjusting at least one parameter of the neural network system to reduce a result of the comparing, for training the neural network system to estimate one of the vocal component and the non-vocal component. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate vocal or instrumental components of an audio signal, depending on which type of component the system is trained to estimate.

Abstract: A system, method and computer product for training a neural network system. The method comprises inputting an audio signal to the system to generate plural outputs f(X, ?). The audio signal includes one or more of vocal content and/or musical instrument content, and each output f(X, ?) corresponds to a respective one of the different content types. The method also comprises comparing individual outputs f(X, ?) of the neural network system to corresponding target signals. For each compared output f(X, ?), at least one parameter of the system is adjusted to reduce a result of the comparing performed for the output f(X, ?), to train the system to estimate the different content types. In one example embodiment, the system comprises a U-Net architecture. After training, the system can estimate various different types of vocal and/or instrument components of an audio signal, depending on which type of component(s) the system is trained to estimate.

Abstract: Systems, methods and computer program products provide dynamic segment resolution and transfer dynamic-segment metadata across media playback devices by detecting a transfer signal indicating a playback session is to be transferred from a first media playback device to a second media playback device, where the playback session contains first dynamic-segment metadata corresponding to a first dynamic-segment having a first data format. Second dynamic-segment metadata corresponding to a second dynamic-segment having a second data format is retrieved and the second media playback device is controlled to play the second dynamic-segment using the second dynamic-segment metadata, where the first data format and the second data format are different.

Abstract: Systems, methods and computer products are provided for retrieving play context. Media content associated with the media content is transmitted over a network. A first media playback device broadcasts an ultrasound code to one or more second media playback devices, where the ultrasound code corresponds to a play context code. The play context code is obtained from a second media playback device and in response the second media playback device receives a play context based on the play context code.

Abstract: An electronic device obtains a plurality of collections of media content items, each collection of media content items being associated with text generated by one or more users of the media-providing service. Based on how frequently a first media content item co-occurs with a first descriptor in text for respective collections of media items that include the first media content item, the electronic device generates, without user input, a new collection of media content items for a first user. The new collection of media content items corresponds to the first descriptor and includes the first media content item. The electronic device presents the new collection of media content items to the first user as a recommendation.

Abstract: A full attention mechanism of a multilingual transformer model is converted into a Longformer attention mechanism to generate a Longformer multilingual transformer model. The Longformer multilingual transformer model is finetuned to perform a summarization task based on episode-description:episode-transcript pairs, thereby generating a finetuned Longformer multilingual transformer model. The Longformer multilingual transformer model also can further be finetuned to perform a summarization task based on article-summary:full-original-article pairs. A summary of a query episode transcript can be generated using the single-finetuned Longformer multilingual transformer model and/or the double-finetuned Longformer multilingual transformer model. The multilingual transformer-based model enables systems, methods and computer products to be capable of generating multilingual abstractive summaries.

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: An architecture is provided for displaying a list of connected devices by generating a first list of devices connected to the same local network and scanning for devices within a defined physical range of a media playback device. A second list of devices within the defined physical range is generated and compared to the first list to create a third list of devices with overlapping identifiers. The media playback device then displays the third list of devices on its interface according to proximity for the user to select an appropriate device for media playback.

Abstract: Audio translation system includes a feature extractor and a style transfer machine learning model. The feature extractor generates for each of a plurality of source voice files one or more source voice parameters encoded as a collection of source feature vectors, and generates for each of a plurality of target voice files one or more target voice parameters encoded as a collection of target feature vectors. The style transfer machine learning model trained on the collection of source feature vectors for the plurality of source voice files and the collection of target feature vectors for the plurality of target voice files to generate a style transformed feature vector.