Patents by Inventor Drew David RIASSETTO

Drew David RIASSETTO 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).

  • MACHINE LEARNING SYSTEM FOR CUSTOMER UTTERANCE INTENT PREDICTION
    Publication number: 20230215426
    Abstract: A method of operating a customer utterance analysis system includes obtaining a subset of utterances from among a first set of utterances. The method includes encoding, by a sentence encoder, the subset of utterances into multi-dimensional vectors. The method includes generating reduced-dimensionality vectors by reducing a dimensionality of the multi-dimensional vectors. Each vector of the reduced-dimensionality vectors corresponds to an utterance from among the subset of utterances. The method includes performing clustering on the reduced-dimensionality vectors. The method includes, based on the clustering performed on the reduced-dimensionality vectors, arranging the subset of utterances into clusters. The method includes obtaining labels for a least two clusters from among the clusters. The method includes generating training data based on the obtained labels. The method includes training a neural network model to predict an intent of an utterance based on the training data.
    Type: Application
    Filed: March 14, 2023
    Publication date: July 6, 2023
    Applicant: TD Ameritrade IP Company, Inc.
    Inventors: Abhilash Krishnankutty NAIR, Amaris Yuseon Sim, Dayanand Narregudem, Drew David Riassetto, Logan Sommers Ahlstrom, Nafiseh Saberian, Stephen Filios, Ravindra Reddy Tappeta Venkata
  • Machine learning system for customer utterance intent prediction
    Patent number: 11626108
    Abstract: A method of operating a customer utterance analysis system includes obtaining a subset of utterances from among a first set of utterances. The method includes encoding, by a sentence encoder, the subset of utterances into multi-dimensional vectors. The method includes generating reduced-dimensionality vectors by reducing a dimensionality of the multi-dimensional vectors. Each vector of the reduced-dimensionality vectors corresponds to an utterance from among the subset of utterances. The method includes performing clustering on the reduced-dimensionality vectors. The method includes, based on the clustering performed on the reduced-dimensionality vectors, arranging the subset of utterances into clusters. The method includes obtaining labels for a least two clusters from among the clusters. The method includes generating training data based on the obtained labels. The method includes training a neural network model to predict an intent of an utterance based on the training data.
    Type: Grant
    Filed: September 25, 2020
    Date of Patent: April 11, 2023
    Assignee: TD Ameritrade IP Company, Inc.
    Inventors: Abhilash Krishnankutty Nair, Amaris Yuseon Sim, Dayanand Narregudem, Drew David Riassetto, Logan Sommers Ahlstrom, Nafiseh Saberian, Stephen Filios, Ravindra Reddy Tappeta Venkata
  • Machine Learning System for Customer Utterance Intent Prediction
    Publication number: 20220101837
    Abstract: A method of operating a customer utterance analysis system includes obtaining a subset of utterances from among a first set of utterances. The method includes encoding, by a sentence encoder, the subset of utterances into multi-dimensional vectors. The method includes generating reduced-dimensionality vectors by reducing a dimensionality of the multi-dimensional vectors. Each vector of the reduced-dimensionality vectors corresponds to an utterance from among the subset of utterances. The method includes performing clustering on the reduced-dimensionality vectors. The method includes, based on the clustering performed on the reduced-dimensionality vectors, arranging the subset of utterances into clusters. The method includes obtaining labels for a least two clusters from among the clusters. The method includes generating training data based on the obtained labels. The method includes training a neural network model to predict an intent of an utterance based on the training data.
    Type: Application
    Filed: September 25, 2020
    Publication date: March 31, 2022
    Inventors: Abhilash Krishnankutty NAIR, Amaris Yuseon SIM, Dayanand NARREGUDEM, Drew David RIASSETTO, Logan Sommers AHLSTROM, Nafiseh SABERIAN, Stephen FILIOS, Ravindra Reddy TAPPETA VENKATA