Abstract: A system and method to provide computer support for a meeting of invitees comprises accessing one or more sensory data streams providing digitized sensory data responsive to an activity of one or more of the invitees during the meeting, the one or more sensory data streams including at least one audio stream. The method also comprises subjecting the at least one audio stream to phonetic and situational computer modeling to recognize a sequence of words in the audio stream and to assign each word to an invitee, subjecting the sequence of words to semantic computer modeling to recognize a sequence of directives in the sequence of words, and releasing one or more output data streams based on the sequence of directives, the one or more output data streams including one or more notifications.

Abstract: A system and method to provide computer support for a meeting of invitees comprises accessing one or more sensory data streams providing digitized sensory data responsive to an activity of one or more of the invitees during the meeting, the one or more sensory data streams including at least one audio stream. The method also comprises subjecting the at least one audio stream to phonetic and situational computer modeling to recognize a sequence of words in the audio stream and to assign each word to an invitee, subjecting the sequence of words to semantic computer modeling to recognize a sequence of directives in the sequence of words, and releasing one or more output data streams based on the sequence of directives, the one or more output data streams including one or more notifications.

Abstract: Disclosed in some examples are methods, systems, machine-readable media, and devices to provide a personalized experience, by making user data available to a skill in a personal assistant service. In an example, a third-party skill such as an automated bot may obtain user data (such as user profile and contextual information at runtime) to personalize and adjust an interaction to the user. Operations to implement the techniques may include: providing a data interface of the personal assistant service to expose user data maintained by the personal assistant service, based on user data privacy settings and third-party skill permissions; receiving a request from the third-party skill, via the data interface, to obtain the user data to in connection with performing some action of the third-party skill; and providing the user data to the third-party skill in response to the request, based on the permission settings and the privacy settings.

Abstract: Aspects of this disclosure provide systems and methods for managing meeting preparation for attendees. In an aspect, preparation events are associated with upcoming meetings. The preparation events are then viewable in association with the meeting or through other preparation interfaces. The technology can determine due dates and work times for the preparation events that allow the user to complete the preparation prior to a scheduled meeting. The due dates and times can be used to surface notifications and reminders of the preparation events. If a meeting is canceled or rescheduled, the due dates for preparation events can automatically be updated.

Abstract: A system and method to provide computer support for a meeting of invitees comprises accessing one or more sensory data streams providing digitized sensory data responsive to an activity of one or more of the invitees during the meeting, the one or more sensory data streams including at least one audio stream. The method also comprises subjecting the at least one audio stream to phonetic and situational computer modeling to recognize a sequence of words in the audio stream and to assign each word to an invitee, subjecting the sequence of words to semantic computer modeling to recognize a sequence of directives in the sequence of words, and releasing one or more output data streams based on the sequence of directives, the one or more output data streams including one or more notifications.

Abstract: Disclosed in some examples are methods, systems, machine-readable media, and devices to provide a personalized experience, by making user data available to a skill in a personal assistant service. In an example, a third-party skill such as an automated bot may obtain user data (such as user profile and contextual information at runtime) to personalize and adjust an interaction to the user. Operations to implement the techniques may include: providing a data interface of the personal assistant service to expose user data maintained by the personal assistant service, based on user data privacy settings and third-party skill permissions; receiving a request from the third-party skill, via the data interface, to obtain the user data to in connection with performing some action of the third-party skill; and providing the user data to the third-party skill in response to the request, based on the permission settings and the privacy settings.

Abstract: A most probable physical meeting location is provided to a user or third-party in response to receiving a subjective reference to the physical meeting location. A collection of physical meeting location values, or objective references to one or more physical meeting locations, are collected based at least in part on sensor data associated with the user. For each subjective reference to a physical meeting location, one or more location clusters comprising objective references to one or more physical meeting locations is generated. As a response to receiving the subjective reference to the physical meeting location, a probable meeting location generated based on cluster density associated with each of the one or more location clusters is provided to the user or third-party.