Microsoft Technology Licensing, LLC

Zhang Li

William B Dolan

Christopher John Brockett

Kaushik Ramaiah Narayanan

Michael Wilson Daniels

Jesse Alexander Freitas

Siqing Chen

Alice Yingming Lai

Warren Anthony Aldred

Christopher Brian Quirk

Domenic J Cipollone

Tomasz Lukasz Religa

Michel Galley

Max Wang

Susan Michele Hendrich

Huitian Jiao

Olivier Gauthier

Si-Qing Chen

Maria Isabel Carpenter

Christine Lauren Mayer

Bhavuk Jain

Juhi Amitkumar Naik

Jing Liu

Cheng Yong Yang

Chin-Yew Lin

Xun Wang

Bogdan Popp

Enrico Cadoni

Mahaveer Bhavarlal Kothari

Alyssa Rachel Mayo

Zeqiu Wu

Peter Kurt Allenspach

Tao Ge

Tashfeen Ahmed

Cheng Yang

Vincent Etter

Sun Mao

Genglin Huang

Tao Wu

Weixin Cai

Xinyu He

Christie Chan

Yizhe Zhang

Utkarsh Garg

Aleksey Aleksandrovich Sokolov

Saket Kumar

Olivier Michel Nicolas Gauthier

Fangrong Chen

Jinge Yao

Si Meng

A data processing system obtains source textual content associated with a first writing style and target textual content associated with a second writing style and provides the source textual content as an input to a first machine learning model which analyzes the source content to determine the first writing style of the first textual content. The system provides an indication of the first writing style and the target textual content as an input to a second machine learning model which analyzes the target textual content and rewrites the target textual content according to the first writing style to output updated target textual content rewritten according to the first writing style. Some implementations utilize a single model trained to receive the source textual content, the target textual content, to determine the writing style of the source textual content and rewrite the target textual content according to the first writing style.

Automatic writing style detection and rewriting

Systems and method directed to assistive document generation are described. More specifically, similar documents share large portions of reusable text structures that can be used to generate an initial document thereby saving a user time. To generate the document, an indication to create the document may be received and based on the indication, a plurality of example documents and grounding content may be identified. Example documents may be existing documents that are similar to a target document of the writer. Grounding information may refer to content that is relevant, timely, and accurate when applied to the target document. The plurality of example documents and the grounding content may be received, and a document sketch based on the example documents and the grounding content may be generated and contains a plurality of predicted text sequences based on the example documents and the grounding content.

Automatic document sketching

A data processing system includes: a processor; a memory containing programming instructions for execution by the processor; and a network interface for communicating with an Artificial Intelligence (AI) engine. The programming instructions include an application for generating written content, the application having a function to generate and submit a structured query regarding the written content to the AI engine to generate feedback on an assessed quality of the written content, the structured query structured to prompt for feedback in a variety of specified categories for the written content. The application further includes a user interface to display the feedback on the written content and provide an option to a user to implement the feedback to revise the written content.

Systems and methods for writing feedback using an artificial intelligence engine

A method and system for providing tone detection for a content may include receiving a request to detect a tone for a content, retrieving user data and data about the content, detecting a content environment for the content based on at least one of the user data and the data about the content, detecting the tone for the content based on the content and the content environment, inputting the content and the detected tone into a machine-learning (ML) model for modifying the tone from the detected tone to a modified tone, obtaining at least one rephrased content segment as an output from the ML model, the rephrased content segment modifying the tone of the content from the detected tone to the modified tone, and providing at least one of the detected tone or the at least one rephrased content segment for display.

Automatic tone detection and suggestion

Systems and methods are directed to generating content that is contextually relevant in a writing style of a user. In example embodiments, a plurality of logical inputs regarding a topic is received in bullet point format. A content generator generates draft content using machine learning (ML) models. The generating comprises identifying a writing style of the user by applying the plurality of logical inputs to a first ML model, determining a context and direction for the draft content using a second ML model, and based on the plurality of logical inputs, the identified writing style, and the context and direction, generating at least one paragraph of draft content in the writing style of the user that follows an outline associated with the bullet point format and comprises a same context and direction as the plurality of logical inputs. The draft content is then presented at a client device.

Automatic content generation

A method and apparatus may be used for document auto-completion. In an aspect, an instruction for creating a document may be received. The document may be presented in response to the instruction, at least a first section in the document including content suggested according to context information associated with the document. An edit operation to the document may be received. Content suggested in response to the edit operation may be presented in at least a second section in the document. In another aspect, context information associated with completion of a document may be identified. Content of at least one section in the document may be generated, the content being suggested based at least on the context information. The content may be presented in the at least one section in the document.

Document auto-completion

An editor service receives a textual input. The editor service provides the textual input to a rule-based grammar checker to obtain a grammar checker result. The editor service also provides the textual input to a machine learning (ML) fluency model that checks the textual input for errors and provides a ML model result. The editor service aggregates the grammar checker result and the ML model result and generates an editor service output based upon the aggregated results. A representation of the editor service result is provided to the client computing system for surfacing through a user interface.

Using editor service to control orchestration of grammar checker and machine learned mechanism

A method and system for providing replacement text segments for a given text segment may include receiving a request to provide the replacement text segment for the text segment in the document, examining a content characteristic of the document, and examining at least one of user-specific information, organization-specific information, or non-linguistic features of the document, before identifying at least one replacement text segment for the text segment, via a machine translation system, based on the content characteristic of the document and at least one of the user-specific information, the organization-specific information, or the non-linguistic features of the document. The method and system may include providing the identified replacement text segment for display to a user, receiving an input indicating a user's selection of the identified replacement text segment, and upon receiving the input, replacing the text segment in the document with the identified replacement text segment.

Method and system for intelligently suggesting paraphrases

A method for providing targeted rewrites can include receiving a selection of text in a file; generating a set of target rewrites of the selection of text, the set of target rewrites comprising: at least one phrase or sentence having semantic similarity to a phrase or sentence of the selection of text; and a style that corresponds to a particular target style, wherein a target style is a representative style for a genre, profession, or environment; and providing for selection one or more of the target rewrites of the set of target rewrites.

Targeted rewrites

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Bellevue, WA, United States of America

Zhang Li