Patents by Inventor Marcello Mendes Hasegawa

Marcello Mendes Hasegawa has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20210365895
    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.
    Type: Application
    Filed: August 5, 2021
    Publication date: November 25, 2021
    Inventors: Robert Alexander SIM, Marcello MENDES HASEGAWA, Ryen William WHITE, Mudit JAIN, Tomer HERMELIN, Adi GERZI ROSENTHAL, Sagi HILLELI
  • Patent number: 11113672
    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.
    Type: Grant
    Filed: March 22, 2018
    Date of Patent: September 7, 2021
    Inventors: Robert Alexander Sim, Marcello Mendes Hasegawa, Ryen William White, Mudit Jain, Tomer Hermelin, Adi Gerzi Rosenthal, Sagi Hilleli
  • Publication number: 20190295041
    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.
    Type: Application
    Filed: March 22, 2018
    Publication date: September 26, 2019
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Robert Alexander SIM, Marcello MENDES HASEGAWA, Ryen William WHITE, Mudit JAIN, Tomer HERMELIN, Adi GERZI ROSENTHAL, Sagi HILLELI
  • Publication number: 20190251417
    Abstract: Techniques for enabling an artificial intelligence system to infer grounded intent from user input, and automatically suggest and/or execute actions associated with the predicted intent. In an aspect, core task descriptions are extracted from actionable statements identified as containing grounded intent. A machine classifier receives the core task description, actionable statements, and user input to predict an intent class for the user input. The machine classifier may be trained using unsupervised learning techniques based on weakly labeled clusters of the core task description extracted over a training corpus. The core task description may include verb-object pairs.
    Type: Application
    Filed: February 12, 2018
    Publication date: August 15, 2019
    Inventors: Paul N Bennett, Marcello Mendes Hasegawa, Nikrouz Ghotbi, Ryen William White, Abhishek Jha
  • Publication number: 20190129749
    Abstract: Automatic extraction and application of conditional tasks from content is provided. A conditional task system includes a classifier that is trained and used to identify conditional tasks and to learn appropriate times and methods to engage a user for reminding the user about conditional tasks. The conditional task system includes components for enabling an automated detection of a conditional task, extracting of attributes that characterize a condition associated with the task, using information about the condition to determine how to monitor for satisfaction of the condition, determining when and how to engage the user about the task, and notifying the user at an appropriate time and using an appropriate method when the condition is satisfied.
    Type: Application
    Filed: November 1, 2017
    Publication date: May 2, 2019
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Ryen William White, Paul Nathan Bennett, Eric Joel Horvitz, Nikrouz Ghotbi, Jason Henry Portenoy, Marcello Mendes Hasegawa, Abhishek Jha, Chaitanya Yashwant Modak