A method, computer program product, and computing system for receiving a signal from each microphone of a plurality of microphones, thus defining a plurality of signals. One or more inter-microphone gain-based augmentations may be performed on the plurality of signals, thus defining one or more inter-microphone gain-augmented signals.

A method, computer program product, and computing system for receiving a signal from each microphone of a plurality of microphones, thus defining a plurality of signals. One or more inter-microphone gain-based augmentations may be performed on the plurality of signals, thus defining one or more inter-microphone gain-augmented signals.

A system and method for real-time fraud detection with a social engineering phoneme (SEP) watchlist of phoneme sequences may perform real-time fraud prevention operations including receiving incoming call interactions and grouping the call interactions into one or more clusters, each cluster associated with a speaker's voice based on voiceprints. For a pair of voiceprints in a cluster, a phoneme sequence is extracted for each voice print. From the extracted phoneme sequences, a similarity score is then calculated to determine if a match exists between the extracted phoneme sequences based on a threshold. If determined a match exists, the phoneme sequence may be added to a SEP watchlist.

A system and method for real-time fraud detection with a social engineering phoneme (SEP) watchlist of phoneme sequences may perform real-time fraud prevention operations including receiving incoming call interactions and grouping the call interactions into one or more clusters, each cluster associated with a speaker's voice based on voiceprints. For a pair of voiceprints in a cluster, a phoneme sequence is extracted for each voice print. From the extracted phoneme sequences, a similarity score is then calculated to determine if a match exists between the extracted phoneme sequences based on a threshold. If determined a match exists, the phoneme sequence may be added to a SEP watchlist.

A method includes obtaining, by a local data system manager of a local data system of the local data systems, a portion of unlabeled data from a local data source, performing, using a domain classifier in the local data system manager, a domain classification analysis on the portion of the unlabeled data to identify a domain of the unlabeled data, making a first determination, based on the domain classification, that the domain classification has significantly varied from a previous domain, based on the first determination: performing an adaptive procedure on a local data system image segmentation model to obtain an adapted image segmentation model, and performing a domain reclassification on the domain classifier to obtain an updated domain classifier, and implementing the adapted image segmentation model on the local data system.

A method includes obtaining, by a local data system manager of a local data system of the local data systems, a portion of unlabeled data from a local data source, performing, using a domain classifier in the local data system manager, a domain classification analysis on the portion of the unlabeled data to identify a domain of the unlabeled data, making a first determination, based on the domain classification, that the domain classification has significantly varied from a previous domain, based on the first determination: performing an adaptive procedure on a local data system image segmentation model to obtain an adapted image segmentation model, and performing a domain reclassification on the domain classifier to obtain an updated domain classifier, and implementing the adapted image segmentation model on the local data system.

Methods, apparatuses, and computer-readable products for selecting tracks. A plurality of request parameters are received from a client device. Based on those request parameters, plurality of bans, history track attributes, and artist identifiers are loaded from a database. A most recent discovery track is calculated based on the plurality of histories and the plurality of artist identifiers. An artist identifier is repeatedly selected from the plurality of artist identifiers along with a track type from a set of track types until a predetermined number of artist identifier and track type pairs have been selected. A plurality of candidate tracks for each selected artist identifier are loaded from a database. One track of the plurality of candidate tracks is repeatedly selected for each artist identifier and track type pair until one track has been selected for each pair of the predetermined number of artist identifier and track type pairs. The predetermined number of tracks that have been selected are returned to the client device.

Systems and methods cause a component of a vehicle to activate. The systems and methods receive audio data generated by a microphone of the vehicle, where the audio data represents sound of the component. Based on the audio data, a condition of the vehicle or the component may be determined, and based on the condition, the vehicle may be commissioned for use or decommissioned.

Systems and methods cause a component of a vehicle to activate. The systems and methods receive audio data generated by a microphone of the vehicle, where the audio data represents sound of the component. Based on the audio data, a condition of the vehicle or the component may be determined, and based on the condition, the vehicle may be commissioned for use or decommissioned.

Method and apparatus for obtaining audio corresponding to a plurality of images, based on semantic information and the emotion information of the plurality of images.