Abstract: Methods, non-transitory machine-readable mediums, and system to provide that a delegate server receives authentication credentials from a first sharee electronic device, determines at least one cryptographic key and metadata accessible to a first sharee corresponding to the received authentication credentials, the metadata defines a set of conditions for a share of location information for an accessory device, evaluates the metadata to determine if the set of conditions are satisfied, upon determination that the set of conditions are satisfied, sends the metadata and the at least one cryptographic key to the first sharee electronic device, receives an indication that a second sharee electronic device is joining the share of location information for the accessory device, and sends at least one update for the cryptographic key and the metadata.

Abstract: Described herein are systems, methods, and apparatus for determining audio context between an audio source and an audio sink and selecting signal profiles based at least in part on that audio context. The signal profiles may include noise cancellation which is configured to facilitate operation within the audio context. Audio context may include user-to-user and user-to-device communications.

Abstract: Described herein are systems, methods, and apparatus for determining audio context between an audio source and an audio sink and selecting signal profiles based at least in part on that audio context. The signal profiles may include noise cancellation which is configured to facilitate operation within the audio context. Audio context may include user-to-user and user-to-device communications.

Abstract: A user can make a symbol with their hand, or other such gesture, at a distance from a computing device that can be captured by at least one imaging element of the device. The captured information can be analyzed to attempt to determine the location of distinguishing features of the symbol in the image information. The image information is then compared to hand gesture information stored in, for example, a library of hand gestures for the user. Upon identifying a match, an input to an application executing on the computing device is provided when the image information contains information matching at least one hand gesture with at least a minimum level of certainty. The hand gesture could include a single “static” gesture, such as a specific letter in sign language, for example, or include two or more “static” gestures. The gesture could also include motion, such as hand movement.

Abstract: Described herein are systems, methods, and apparatus for determining audio context between an audio source and an audio sink and selecting signal profiles based at least in part on that audio context. The signal profiles may include noise cancellation which is configured to facilitate operation within the audio context. Audio context may include user-to-user and user-to-device communications.

Abstract: Described herein are systems and methods for context-aware speech processing. A speech context is determined based on context data associated with a user uttering speech. The speech context and the speech uttered in that speech context may be used to build acoustic models for that speech context. An acoustic model for use in speech processing may be selected based on the determined speech context. A language model for use in speech processing may also be selected based on the determined speech context. Using the acoustic and language models, the speech may be processed to recognize the speech from the user.

Abstract: Described herein are systems, methods, and apparatus for determining audio context between an audio source and an audio sink and selecting signal profiles based at least in part on that audio context. The signal profiles may include noise cancellation which is configured to facilitate operation within the audio context. Audio context may include user-to-user and user-to-device communications.

Abstract: A user can make a symbol with their hand, or other such gesture, at a distance from a computing device that can be captured by at least one imaging element of the device. The captured information can be analyzed to attempt to determine the location of distinguishing features of the symbol in the image information. The image information is then compared to hand gesture information stored in, for example, a library of hand gestures for the user. Upon identifying a match, an input to an application executing on the computing device is provided when the image information contains information matching at least one hand gesture with at least a minimum level of certainty. The hand gesture could include a single “static” gesture, such as a specific letter in sign language, for example, or include two or more “static” gestures. The gesture could also include motion, such as hand movement.

Abstract: A user can make a symbol with their hand, or other such gesture, at a distance from a computing device that can be captured by at least one imaging element of the device. The captured information can be analyzed to attempt to determine the location of distinguishing features of the symbol in the image information. The image information is then compared to hand gesture information stored in, for example, a library of hand gestures for the user. Upon identifying a match, an input to an application executing on the computing device is provided when the image information contains information matching at least one hand gesture with at least a minimum level of certainty. The hand gesture could include a single “static” gesture, such as a specific letter in sign language, for example, or include two or more “static” gestures. The gesture could also include motion, such as hand movement.