Microsoft Technology Licensing, LLC

Nikrouz Ghotbi

Ryen William White

Christian Liensberger

Marcus A Ash

Nirupama Chandrasekaran

Lisa Joy Stifelman

August Kathryn Niehaus

Aleksandar Antonijevic

Vashutosh Agrawal

Sachin Venugopalan

Tvrtko Tadic

Eric J Horvitz

Michael Gamon

Paul Nathan Bennett

Robert Alexander Sim

Patrick Pantel

Mark James Encarnacion

Richard Lloyd Hughes

Ajoy Nandi

Prabhdeep Singh

Eddie Fusaro

Anantha Deepthi Uppala

Vanessa Graham Murdock

Jason T Creighton

John Alton Price

Mathieu Etienne Jacques Audouin

Jeff Roger DeVries

Techniques are described herein that are capable of performing intent-based scheduling via a digital personal assistant. For instance, an intent of user(s) to perform an action (a.k.a. activity) may be used to schedule time (e.g., on a calendar of at least one of the user(s)) in which the action is to be performed. Examples of performing an action include but are not limited to having a meeting, working on a project, participating in a social event, exercising, and reading.

Intent-based scheduling via digital personal assistant

Disclosed in some examples are methods, systems, machine-readable media, and devices which provide for real-time personalized suggestions for participants in a network-based communication service. The personalized suggestions may include options for taking actions, content suggestions, and smart replies. These suggestions may be based upon the current conversation and are delivered personally to each participant.

Real-time personalized suggestions for communications between participants

Task assignments are identified. A dataset that includes one or more electronic messages is received. Then, one or more pending tasks in the dataset are identified, and each of a plurality of people who are mentioned in the dataset is also identified. Then, for each of the pending tasks, one or more of the identified people are identified as potentially being people who are assigned to complete the pending task, and the pending task is associated with these identified one or more of the identified people. For each of the pending tasks, one or more of the identified people are also identified as potentially being people for whom the pending task is to be completed, and the pending task is also associated with these identified one or more of the identified people.

Identifying task assignments

Intent-based calendar updating via digital personal assistant

Generating talking points on behalf of a user and providing the talking points to the user is provided. Talking points can help users to quickly and easily start a personalized conversation that enables participants of the conversation to make a connection, thus eliciting better communication and collaboration. Talking points can be generated based on commitments or requests identified in a previous conversation, anomalies or patterns identified in context data, or information items of interest collected from various data sources. One or more top-ranking talking points are surfaced to the user to help the user start a new conversation or to continue a previous conversation.

Contextually inferred talking points for improved communication

Methods, systems, and computer programs are presented for a smart communications assistant with an audio interface. One method includes an operation for getting messages addressed to a user. The messages are from one or more message sources and each message comprising message data that includes text. The method further includes operations for analyzing the message data to determine a meaning of each message, for generating a score for each message based on the respective message data and the meaning of the message, and for generating a textual summary for the messages based on the message scores and the meaning of the messages. A speech summary is created based on the textual summary and the speech summary is then sent to a speaker associated with the user. The audio interface further allows the user to verbally request actions for the messages.

Smart communications assistant with audio interface

Aspects of the technology described herein provide an efficient user interface that enables users to respond to tasks quickly by providing automated quick task notifications via an audio channel. An audio channel quick task system includes components for recognizing and extracting quick tasks from content (e.g., interpersonal communications, composed content, line of business (LOB) application documents), and for prioritizing and routing the quick tasks to the user via an audio channel at an appropriate and relevant time. The system is enabled to process a user response, determine an action for handling the quick task, and execute the action on behalf of the user (e.g., pass a reply to a requestor, pass an instruction to an application or service, queue the quick task notification, delegate the quick task to another user or bot, forward the quick task to a companion device, or launch an application on a companion device).

Automated quick task notifications via an audio channel

Apparatus and methods can be implemented to determine correctness and/or consistency of communications in a variety of applications. In various embodiments, a communication in a communication channel can be monitored, a feature from the monitored communication can be extracted for comparison with one or more sample features to determine correctness and/or an identification of a contradiction of the extracted feature from which remedial action can be taken. Additional apparatus, systems, and methods are disclosed.

Identification and notification of correctness and contradiction in communications

A Personal Virtual Assistant (PVA) system takes existing inputs and processes them to understand the user's personality, intent, etc., through analysis of features such as the user's tone, language use, vocal volume, facial expressions, and context from device use and surroundings. As a result of the processing, the PVA system augments how it responds and interacts with the user. Such augmented responses may include simple things like changing the assistant's tone to complimenting the user's mood, as well as changing her use of language, volume, and the way she shares information, like giving good news when the user might be down, or suppressing bad news when the time is not right for the user to optimally process it.

Empathetic personal virtual digital assistant

A system that analyses content of electronic communications may automatically extract requests or commitments from the electronic communications. In one example process, a processing component may analyze the content to determine one or more meanings of the content; query content of one or more data sources that is related to the electronic communications; and based, at least in part, on (i) the one or more meanings of the content and (ii) the content of the one or more data sources, automatically identify and extract a request or commitment from the content. Multiple actions may follow from initial recognition and extraction, including confirmation and refinement of the description of the request or commitment, and actions that assist one or more of the senders, recipients, or others to track and address the request or commitment, including the creation of additional messages, reminders, appointments, or to-do lists.

Automatic extraction of commitments and requests from communications and content

Growing community of inventors

Redmond, WA, United States of America

Nikrouz Ghotbi