Patents by Inventor Xinyun Zhao

Xinyun Zhao 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).

  • Patent number: 11243853
    Abstract: Technology for determining an amount of time to wait to retry requests to a representational state transfer (REST) server system for a REST resource, where the time to wait is always chosen to be a prime number of time units (for example, slots, milliseconds). While currently conventional systems will sometimes use a prime number of time units to wait for a retry request, various embodiments of the present invention will always, and invariably, use a prime number of time units. The REST resource may be, for example, a REST application programming interface (API) that is requested by and delivered to a client system using hypertext transfer protocol (HTTP).
    Type: Grant
    Filed: November 26, 2019
    Date of Patent: February 8, 2022
    Assignee: International Business Machines Corporation
    Inventors: Stefan A. G. van Der Stockt, Joseph Lindsey Sharpe, III, Xinyun Zhao, Sihang Bob Fang, Manali Jairam Chanchlani, Rahul P. Akolkar, Sai Karthik Reddy Ginni, Kristi Farinelli
  • Patent number: 11057231
    Abstract: A prescriptive meeting resource recommendation engine automatically learns participant and resource preferences in the context of given meeting input data using natural language features, and automatically recommends all relevant participants and resources (teleconferences, web meetings, links, etc.) to the meeting creator. The engine uses a feature data store to associate historical persons and historical resources with various natural language features, e.g., chargrams. As the host enters text in an invitation template (such as in the title field), the engine extracts current natural language features and computes current participant scores and current resource scores based on the current natural language features. A “forgetfulness” routine is applied to the feature data store to phase out the influence of stale data.
    Type: Grant
    Filed: August 28, 2018
    Date of Patent: July 6, 2021
    Assignee: International Business Machines Corporation
    Inventors: Rahul P. Akolkar, Brian E. Bissell, Kristi A. Farinelli, Joseph L. Sharpe, III, Stefan Van Der Stockt, Xinyun Zhao
  • Publication number: 20210157688
    Abstract: Technology for determining an amount of time to wait to retry requests to a representational state transfer (REST) server system for a REST resource, where the time to wait is always chosen to be a prime number of time units (for example, slots, milliseconds). While currently conventional systems will sometimes use a prime number of time units to wait for a retry request, various embodiments of the present invention will always, and invariably, use a prime number of time units. The REST resource may be, for example, a REST application programming interface (API) that is requested by and delivered to a client system using hypertext transfer protocol (HTTP).
    Type: Application
    Filed: November 26, 2019
    Publication date: May 27, 2021
    Inventors: Stefan A.G. van Der Stockt, Joseph Lindsey Sharpe, III, Xinyun Zhao, Sihang Bob Fang, Manali Jairam Chanchlani, Rahul P. Akolkar, Sai Karthik Reddy Ginni, Kristi Farinelli
  • Patent number: 11017774
    Abstract: A method, system, and computer program product are provided for classifying spoken audio content with a cognitive audio classifier by applying a set of distorted audio resources through a set of speech-to-text models STTi (STT1 . . . STTn) to get a set of interference coherence scores based on the transcript for each speech-to-text model STTi, thereby generating a measured baseline Mi (M1 . . . Mn) and a practical baseline Pi (P1 . . . Pn) that is associated with a coherence matrix for the audio effects AEj (AE1 . . . AEk) that were used to generate the distorted audio resources, thereby generating training data for use in training a cognitive audio classifier which classifies input spoken audio content to measure a quality of detected vocabulary elements from the spoken audio content under the set of audio distortion effects for each speech-to-text model STTi.
    Type: Grant
    Filed: February 4, 2019
    Date of Patent: May 25, 2021
    Assignee: International Business Machines Corporation
    Inventors: Kristi A. Farinelli, Rahul P. Akolkar, Brian E. Bissell, Joseph L. Sharpe, III, Stefan van der Stockt, Xinyun Zhao
  • Publication number: 20200251115
    Abstract: A method, system, and computer program product are provided for classifying spoken audio content with a cognitive audio classifier by applying a set of distorted audio resources through a set of speech-to-text models STTi (STT1 . . . STTn) to get a set of interference coherence scores based on the transcript for each speech-to-text model STTi, thereby generating a measured baseline Mi (M1 . . . Mn) and a practical baseline Pi (P1 . . . Pn) that is associated with a coherence matrix for the audio effects AEj (AE1 . . . AEk) that were used to generate the distorted audio resources, thereby generating training data for use in training a cognitive audio classifier which classifies input spoken audio content to measure a quality of detected vocabulary elements from the spoken audio content under the set of audio distortion effects for each speech-to-text model STTi.
    Type: Application
    Filed: February 4, 2019
    Publication date: August 6, 2020
    Inventors: Kristi A. Farinelli, Rahul P. Akolkar, Brian E. Bissell, Joseph L. Sharpe, III, Stefan van der Stockt, Xinyun Zhao
  • Publication number: 20200076634
    Abstract: A prescriptive meeting resource recommendation engine automatically learns participant and resource preferences in the context of given meeting input data using natural language features, and automatically recommends all relevant participants and resources (teleconferences, web meetings, links, etc.) to the meeting creator. The engine uses a feature data store to associate historical persons and historical resources with various natural language features, e.g., chargrams. As the host enters text in an invitation template (such as in the title field), the engine extracts current natural language features and computes current participant scores and current resource scores based on the current natural language features. A “forgetfulness” routine is applied to the feature data store to phase out the influence of stale data.
    Type: Application
    Filed: August 28, 2018
    Publication date: March 5, 2020
    Inventors: Rahul P. Akolkar, Brian E. Bissell, Kristi A. Farinelli, Joseph L. Sharpe, III, Stefan Van Der Stockt, Xinyun Zhao