Microsoft Technology Licensing, LLC

Aleksandar Antonijevic

Hang Li

Ling Tony Chen

Lisa Joy Stifelman

Vashutosh Agrawal

Sachin Venugopalan

Leonardo Esteban Blanco

Brendan Joseph Clark

Blake Douglas Pelton

Nikrouz Ghotbi

August Kathryn Niehaus

Tvrtko Tadic

Silvana Patricia Moncayo

Max Alan McMullen

Anuj Bharat Gosalia

Djordje Nijemcevic

Benjamin C Constable

Daniel Wood

Joshua Warren Priestley

Jesse Bishop

Ivan Mitic

Mircea Cimpoi

Imran Majid

Mary Luo

Vidhya Sriram

Meng Yang

Leah M Keegan

Adrian A Mascarenhas

Daniel C Rischar

Bede A Jordan

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

Atlasing and virtual surface techniques are described. In one or more implementations, virtual surface functionality is exposed by an operating system for access by one or more applications of the computing device. A virtual surface is created in response to a request from the one or more applications to be used to render visuals for display by a display device. The virtual surface is allocated in memory of the computing device by the exposed virtual surface functionality to have an area that is larger than an area to be used to display the visuals from the one or more applications.

Atlasing and virtual surfaces

A method for identifying words in a textual image undergoing optical character recognition includes receiving a bitmap of an input image which includes textual lines that have been segmented by a plurality of chop lines. The chop lines are each associated with a confidence level reflecting a degree to which the respective chop line properly segments the textual line into individual characters. One or more words are identified in one of the textual lines based at least in part on the textual lines and a first subset of the plurality of chop lines which have a chop line confidence level above a first threshold value. If the first word is not associated with a sufficiently high word confidence level, at least a second word in the textual line is identified based at least in part on a second subset of the plurality of chop lines which have a confidence level above a second threshold value lower than the first threshold value.

Word recognition of text undergoing an OCR process

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Bellevue, WA, United States of America

Aleksandar Antonijevic