Abstract: In one embodiment, a method includes detecting a user input comprising an incomplete gesture performed by one or more hands of a first user by a client system associated with the first user; selecting one or more candidate gestures from a plurality of pre-defined gestures by the client system based on a personalized gesture-recognition model, wherein each of the candidate gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate gesture, and presenting one or more suggested inputs corresponding to one or more of the candidate gestures at the client system.

Abstract: In one embodiment, a method includes receiving a user request from a first user from a client system associated with a first user, wherein the user request comprise a gesture-input from the first user and a speech-input from the first user, determining an intent corresponding to the user request based on the gesture-input by a personalized gesture-classification model associated with the first user, executing one or more tasks based on the determined intent and the speech-input, and sending instructions for presenting execution results of the one or more tasks to the client system responsive the user request.

Abstract: In one embodiment, a method includes receiving an initial input in a first modality from a first user at a client system, determining intents and slots corresponding to the initial input, wherein the slots are conditioned on the intents, generating one or more candidate continuation-inputs based on the intents and slots, where the one or more candidate continuation-inputs are in one or more candidate modalities, respectively, wherein the candidate modalities are different from the first modality, and wherein each of the candidate continuation-inputs references entities represented by the slots, and presenting one or more suggested inputs corresponding to one or more of the candidate continuation-inputs at the client system.

Abstract: In one embodiment, a method includes receiving an initial input in a first modality from a first user from a client system associated with the first user, determining one or more intents corresponding to the initial input by an intent-understanding module, generating one or more candidate continuation-inputs based on the one or more intents, where the one or more candidate continuation-inputs are in one or more candidate modalities, respectively, and wherein the candidate modalities are different from the first modality, and sending instructions for presenting one or more suggested inputs corresponding to one or more of the candidate continuation-inputs to the client system.

Abstract: Systems, methods, and non-transitory computer-readable media can receive at least one request for performing one or more operations, the request originating from a media application running on a media device, the request being broadcasted by the media device over a network to which the computing device is also connected. Information describing the request can be provided through a software application running on the computing device. A determination is made when user operating the computing device has approved the request. The operations are performed by at least the software application running on the computing device.

Abstract: In one embodiment, a method includes maintaining a reminder store comprising one or more reminders for a first user, wherein each reminder is associated with an initial activation-condition, determining a context associated with the first user based on signals from a client system associated with the first user, determining a suppression-condition associated with at least one of the reminders is met based on the context, and suppressing the at least one reminder for the first user.

Abstract: In one embodiment, a method includes receiving an instruction to add an assistant xbot as a participant in a conversation thread from a first user of a plurality of users participating in the conversation thread, monitoring the conversation thread including user inputs by one or more users of the plurality of users via the assistant xbot, analyzing the user inputs to identify intents based on a natural-language understanding module, sending instructions for prompting one or more users of the plurality of users to provide information for completing tasks associated with the intents via the assistant xbot within the conversation thread, executing the tasks based on the information provided by one or more agents, and sending instructions for presenting information associated with one or more of the executed tasks via the assistant xbot within the conversation thread.

Abstract: Within a social network, a user may establish a set of contacts who share with the user various content items and comments related thereto. However, these content items are often hosted by a content source outside of the social network, and the user may have to transition to the content source to view the content item, and then transition back to the social network to submit a comment. Instead, a device may monitor the social network to record shared content items. When the user requests a presentation of the content source, the content items hosted by the content source that have been shared with the user may be included in the presentation. The presentation of the content source may also accept comments from the user regarding a content item, and send the comments to the social network where the content item was shared with the user.

Abstract: In one embodiment, a method includes receiving a user request from a first user from a client system associated with a first user, wherein the user request comprise a gesture-input from the first user and a speech-input from the first user, determining an intent corresponding to the user request based on the gesture-input by a personalized gesture-classification model associated with the first user, executing one or more tasks based on the determined intent and the speech-input, and sending instructions for presenting execution results of the one or more tasks to the client system responsive the user request.

Abstract: In one embodiment, a method includes detecting a user input comprising an incomplete gesture performed by one or more hands of a first user by a client system associated with the first user; selecting one or more candidate gestures from a plurality of pre-defined gestures by the client system based on a personalized gesture-recognition model, wherein each of the candidate gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate gesture, and presenting one or more suggested inputs corresponding to one or more of the candidate gestures at the client system.

Abstract: In accordance with one or more aspects of selecting between client-side and server-side market detection, a determination is made at a device as to which of a client-side detected market and a server-side detected market is to have priority for a service. An application of the device is configured in accordance with a client-side market configuration setting if the client-side detected market has priority, and is configured in accordance with a server-side market configuration setting if the server-side detected market has priority.

Abstract: A method described herein includes acts of extracting at least one entity from an arbitrary web page being viewed by an individual on a computing device and comparing the at least one entity with social network data of the individual, wherein the social network data comprises a plurality of messages generated by members of a social network of the individual. The method further includes the acts of identifying at least one message in the plurality of messages based at least in part upon the comparing of the at least one entity with the social network data of the individual and causing the at least one message to be displayed on the web page in conjunction with the at least one entity.

Abstract: In one embodiment, a method includes accessing a plurality of input tuples associated with a first user from a data store, wherein each input tuple comprises a gesture-input and a corresponding speech-input, determining a plurality of intents corresponding to the plurality of speech-inputs, respectively, by a natural-language understanding (NLU) module, generating a plurality of feature representations for the plurality of gesture-inputs based on one or more machine-learning models, determining a plurality of gesture identifiers for the plurality of gesture-inputs, respectively, based on their respective feature representations, associating the plurality of intents with the plurality of gesture identifiers, respectively, and training a personalized gesture-classification model for the first user based on the plurality of feature representations of their respective gesture-inputs and the associations between the plurality of intents and their respective gesture identifiers.

Abstract: In one embodiment, a method includes receiving a user input from a client system associated with a first user, wherein the user input comprises an incomplete gesture performed by the first user, calculating one or more confidence scores by an intent-understanding module for one or more intents corresponding to the incomplete gesture, determining the calculated confidence scores associated with each of the intents are below a threshold score, selecting candidate gestures from a plurality of pre-defined gestures based on a personalized gesture-recognition model responsive to determining that the calculated confidence scores for each of the intents are below the threshold score, wherein each of the candidate gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate gesture, and sending instructions for presenting one or more suggested inputs corresponding to one or more of the candidate gestures to the client system.

Abstract: The various embodiments described herein include methods and/or systems for depth mapping. In one aspect, a method of depth mapping is performed at an apparatus including a projector, a camera, one or more processors, and memory storing one or more programs for execution by the one or more processors. The method includes identifying one or more areas of interest in a scene in accordance with variation of depth in the scene as detected at a first resolution. The method also includes, for each area of interest: (1) applying, via the projector, a respective structured-light pattern to the area of interest; (2) capturing, via the camera, an image of the area of interest with the respective structured-light pattern applied to it; and (3) creating a respective depth map of the area of interest using the captured image, the respective depth map having a higher resolution than the first resolution.

Abstract: In accordance with one or more aspects of selecting between client-side and server-side market detection, a determination is made at a device as to which of a client-side detected market and a server-side detected market is to have priority for a service. An application of the device is configured in accordance with a client-side market configuration setting if the client-side detected market has priority, and is configured in accordance with a server-side market configuration setting if the server-side detected market has priority.

Abstract: Systems, methods, and non-transitory computer-readable media can receive at least one request for performing one or more operations, the request originating from a media application running on a media device, the request being broadcasted by the media device over a network to which the computing device is also connected. Information describing the request can be provided through a software application running on the computing device. A determination is made when user operating the computing device has approved the request. The operations are performed by at least the software application running on the computing device.

Abstract: Systems, methods, and non-transitory computer-readable media can receive at least one request for performing one or more operations, the request originating from a media application running on a media device, the request being broadcasted by the media device over a network to which the computing device is also connected. Information describing the request can be provided through a software application running on the computing device. A determination is made when user operating the computing device has approved the request. The operations are performed by at least the software application running on the computing device.

Abstract: In one embodiment, a method includes accessing a plurality of input tuples associated with a first user from a data store, wherein each input tuple comprises a gesture-input and a corresponding speech-input, determining a plurality of intents corresponding to the plurality of speech-inputs, respectively, by a natural-language understanding (NLU) module, generating a plurality of feature representations for the plurality of gesture-inputs based on one or more machine-learning models, determining a plurality of gesture identifiers for the plurality of gesture-inputs, respectively, based on their respective feature representations, associating the plurality of intents with the plurality of gesture identifiers, respectively, and training a personalized gesture-classification model for the first user based on the plurality of feature representations of their respective gesture-inputs and the associations between the plurality of intents and their respective gesture identifiers.

Abstract: In one embodiment, a method includes receiving a user input from a client system associated with a first user, wherein the user input comprises an incomplete gesture performed by the first user, calculating one or more confidence scores by an intent-understanding module for one or more intents corresponding to the incomplete gesture, determining the calculated confidence scores associated with each of the intents are below a threshold score, selecting candidate gestures from a plurality of pre-defined gestures based on a personalized gesture-recognition model responsive to determining that the calculated confidence scores for each of the intents are below the threshold score, wherein each of the candidate gestures is associated with a confidence score representing a likelihood the first user intended to input the respective candidate gesture, and sending instructions for presenting one or more suggested inputs corresponding to one or more of the candidate gestures to the client system.