A service management system communicates via wide area network with gateway devices located at respective user premises. The service management system remotely manages delivery of application services, which can be voice controlled, by a gateway, e.g. by selectively activating/deactivating service logic modules in the gateway. The service management system also may selectively provide secure communications and exchange of information among gateway devices and among associated endpoint devices. An exemplary service management system includes a router connected to the network and one or more computer platforms, for implementing management functions. Examples of the functions include a connection manager for controlling system communications with the gateway devices, an authentication manager for authenticating each gateway device and controlling the connection manager and a subscription manager for managing applications services and/or features offered by the gateway devices. A service manager, controlled by the subscription manager, distributes service specific configuration data to authenticated gateway devices.

Audio content episodes are received. Using machine learning, one or more audio segments of interest are identified in each of the audio content episodes based at least in part on an analysis of content included in a corresponding audio content episode. Each of the identified audio segments is associated with one or more automatically determined tags. Using machine learning, a recommended audio segment is selected for a specific user from the identified audio segments based at least in part on attributes of the specific user and the automatically determined tags of the identified audio segments. The recommended audio segment are automatically provided in an audio segment feed.

Audio content episodes are received. Using machine learning, one or more audio segments of interest are identified in each of the audio content episodes based at least in part on an analysis of content included in a corresponding audio content episode. Each of the identified audio segments is associated with one or more automatically determined tags. Using machine learning, a recommended audio segment is selected for a specific user from the identified audio segments based at least in part on attributes of the specific user and the automatically determined tags of the identified audio segments. The recommended audio segment are automatically provided in an audio segment feed.

Embodiments are disclosed for performing a section-based, within-song music similarity search by an audio recommendation system. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving an input including an audio sequence and a request to determine similar audio sequences to the audio sequence from a pre-processed audio catalog, analyzing the audio sequence to generate an audio embedding for the audio sequence, querying a pre-processed audio catalog to retrieve audio embeddings for catalog audio sequences at different time resolutions, generating a set of candidate audio sequences from the pre-processed audio catalog based on the audio embedding for the audio sequence, and providing the set of candidate audio sequences.

Embodiments are disclosed for performing a section-based, within-song music similarity search by an audio recommendation system. In particular, in one or more embodiments, the disclosed systems and methods comprise receiving an input including an audio sequence and a request to determine similar audio sequences to the audio sequence from a pre-processed audio catalog, analyzing the audio sequence to generate an audio embedding for the audio sequence, querying a pre-processed audio catalog to retrieve audio embeddings for catalog audio sequences at different time resolutions, generating a set of candidate audio sequences from the pre-processed audio catalog based on the audio embedding for the audio sequence, and providing the set of candidate audio sequences.

Methods, systems, and computer programs for generating a queue of media content items to be played in a party setting are described. A first seed track is identified and is used to create a plurality of related media content items that are presented to a plurality of voters. The media content item receiving the most votes is placed in the queue and subsequently played.

Methods, systems, and computer programs for generating a queue of media content items to be played in a party setting are described. A first seed track is identified and is used to create a plurality of related media content items that are presented to a plurality of voters. The media content item receiving the most votes is placed in the queue and subsequently played.

An audio record management method includes linking an app dedicated for audio record management installed in a first device and a website dedicated for audio record management connected to a second device; displaying an audio file being recorded or being played back in the app on a file list on the website through linkage between the app and the website; and providing a memo creation screen for the audio file on the website in response to a selection of the audio file from the file list.

An audio record management method includes linking an app dedicated for audio record management installed in a first device and a website dedicated for audio record management connected to a second device; displaying an audio file being recorded or being played back in the app on a file list on the website through linkage between the app and the website; and providing a memo creation screen for the audio file on the website in response to a selection of the audio file from the file list.

Systems and methods for identifying the most impactful moments or segments of music, which are those most likely to elicit a chills effect in a human listener. A digital music signal is processed using two or more objective processing metrics that measure acoustic features known to be able to elicit the chills effect. Individual detection events are identified in the output of each metric based on the output being above or below thresholds relative to the overall output. A combination algorithm aggregates concurrent detection events to generate a continuous concurrence data set of the number of concurrent detection events during the music signal, which can be calculated per beat. A phrase detection algorithm can identify impactful segments of the music based on at least one of peaks, peak-proximity, and a moving average of the continuous concurrence data.