The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Sep. 02, 2025
Filed:
Jun. 23, 2023
Microsoft Technology Licensing, Llc, Redmond, WA (US);
Xiao Yan Lu, Bellevue, WA (US);
Amir Kantor, Haifa, IL;
Ido Priness, Kiryat Ono, IL;
Shiraz Jitendra Cupala, Snohomish, WA (US);
Kevin Michael Carter, Atlanta, GA (US);
Adi Miller, Ramat Hasharon, IL;
Kumud Ranjan, Redmond, WA (US);
Shyam Gupta, Surrey, CA;
Gautam Jain, Surrey, CA;
Yasemin Cenberoglu, Montreal, CA;
Shai Ifrach, Yavne, IL;
Shlomi Maliah, Rosh Hayin, IL;
Gilad Gildin, Tel Aviv, IL;
Ofek David, Tel-Aviv, IL;
Eleonora Shtotland, Herzliya, IL;
Jaime Teevan, Bellevue, WA (US);
Matthew Jonathan Gardner, Irvine, CA (US);
Lan Ye, Issaquah, WA (US);
Microsoft Technology Licensing, LLC, Redmond, WA (US);
Abstract
A system for providing a personalized assistant within a network-based communication session includes a processor and a memory storage device storing instructions. The system determines when a first communication session participant joins the network-based communication session after a threshold duration of time subsequent to the start time of the session. Upon determining the first participant has joined, the system obtains content associated with the session and creates request data for a pre-trained generative language model. The request data includes an instruction requesting a predetermined number of suggested utterances not present in the content, each utterance relating to one or more topics corresponding to the content. The system transforms the request data to a command based on a command template and provides the command to the generative language model. The system receives a response from the model, including the predetermined number of suggested utterances, and presents them to the communication session participant in a graphical user interface while the session is in session.