Patents by Inventor Tomer ROSENTHAL

Tomer ROSENTHAL 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).

  • Determining topic labels for communication transcripts based on a trained generative summarization model
    Patent number: 11630958
    Abstract: The disclosure herein describes determining topics of communication transcripts using trained summarization models. A first communication transcript associated with a first communication is obtained and divided into a first set of communication segments. A first set of topic descriptions is generated based on the first set of communication segments by analyzing each communication segment of the first set of communication segments with a generative language model. A summarization model is trained using the first set of communication segments and associated first set of topic descriptions as training data. The trained summarization model is then applied to a second communication transcript and, based on applying the trained summarization model to the second communication transcript, a second set of topic descriptions of the second communication transcript is generated.
    Type: Grant
    Filed: June 2, 2021
    Date of Patent: April 18, 2023
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Royi Ronen, Yarin Kuper, Tomer Rosenthal, Abedelkader Asi, Erez Altus, Rona Shaanan
  • DETERMINING TOPIC LABELS FOR COMMUNICATION TRANSCRIPTS BASED ON A TRAINED GENERATIVE SUMMARIZATION MODEL
    Publication number: 20220391591
    Abstract: The disclosure herein describes determining topics of communication transcripts using trained summarization models. A first communication transcript associated with a first communication is obtained and divided into a first set of communication segments. A first set of topic descriptions is generated based on the first set of communication segments by analyzing each communication segment of the first set of communication segments with a generative language model. A summarization model is trained using the first set of communication segments and associated first set of topic descriptions as training data. The trained summarization model is then applied to a second communication transcript and, based on applying the trained summarization model to the second communication transcript, a second set of topic descriptions of the second communication transcript is generated.
    Type: Application
    Filed: June 2, 2021
    Publication date: December 8, 2022
    Inventors: Royi RONEN, Yarin KUPER, Tomer ROSENTHAL, Abedelkader ASI, Erez ALTUS, Rona SHAANAN