Patents by Inventor Zhenxiang Zhou

Zhenxiang Zhou 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).

  • Learning how to rewrite user-specific input for natural language understanding
    Patent number: 11862149
    Abstract: Techniques for decreasing (or eliminating) the possibility of a skill performing an action that is not responsive to a corresponding user input are described. A system may train one or more machine learning models with respect to user inputs, which resulted in incorrect actions being performed by skills, and corresponding user inputs, which resulted in the correct action being performed. The system may use the trained machine learning model(s) to rewrite user inputs that, if not rewritten, may result in incorrect actions being performed. The system may implement the trained machine learning model(s) with respect to ASR output text data to determine if the ASR output text data corresponds (or substantially corresponds) to previous ASR output text data that resulted in an incorrect action being performed.
    Type: Grant
    Filed: September 2, 2021
    Date of Patent: January 2, 2024
    Assignee: Amazon Technologies, Inc.
    Inventors: Bigyan Rajbhandari, Praveen Kumar Bodigutla, Zhenxiang Zhou, Karen Catelyn Stabile, Chenlei Guo, Abhinav Sethy, Alireza Roshan Ghias, Pragaash Ponnusamy, Kevin Quinn
  • LEARNING HOW TO REWRITE USER-SPECIFIC INPUT FOR NATURAL LANGUAGE UNDERSTANDING
    Publication number: 20220059086
    Abstract: Techniques for decreasing (or eliminating) the possibility of a skill performing an action that is not responsive to a corresponding user input are described. A system may train one or more machine learning models with respect to user inputs, which resulted in incorrect actions being performed by skills, and corresponding user inputs, which resulted in the correct action being performed. The system may use the trained machine learning model(s) to rewrite user inputs that, if not rewritten, may result in incorrect actions being performed. The system may implement the trained machine learning model(s) with respect to ASR output text data to determine if the ASR output text data corresponds (or substantially corresponds) to previous ASR output text data that resulted in an incorrect action being performed.
    Type: Application
    Filed: September 2, 2021
    Publication date: February 24, 2022
    Inventors: Bigyan Rajbhandari, Praveen Kumar Bodigutla, Zhenxiang Zhou, Karen Catelyn Stabile, Chenlei Guo, Abhinav Sethy, Alireza Roshan Ghias, Pragaash Ponnusamy, Kevin Quinn
  • Learning how to rewrite user-specific input for natural language understanding
    Patent number: 11151986
    Abstract: Techniques for decreasing (or eliminating) the possibility of a skill performing an action that is not responsive to a corresponding user input are described. A system may train one or more machine learning models with respect to user inputs, which resulted in incorrect actions being performed by skills, and corresponding user inputs, which resulted in the correct action being performed. The system may use the trained machine learning model(s) to rewrite user inputs that, if not rewritten, may result in incorrect actions being performed. The system may implement the trained machine learning model(s) with respect to ASR output text data to determine if the ASR output text data corresponds (or substantially corresponds) to previous ASR output text data that resulted in an incorrect action being performed.
    Type: Grant
    Filed: September 21, 2018
    Date of Patent: October 19, 2021
    Assignee: Amazon Technologies, Inc.
    Inventors: Bigyan Rajbhandari, Praveen Kumar Bodigutla, Zhenxiang Zhou, Karen Catelyn Stabile, Chenlei Guo, Abhinav Sethy, Alireza Roshan Ghias, Pragaash Ponnusamy, Kevin Quinn