公开(公告)号：US12197871B2

公开(公告)日：2025-01-14

申请号：US17973674

申请日：2022-10-26

Applicant: Amazon Technologies, Inc.

Inventor： Pavel Bhowmik ,  Melanie C B Gens ,  Sachin Midha ,  Rahul Gupta ,  Sriram Venkatapathy ,  Xinhong Zhang ,  Anoop Kumar ,  Pooja Sanjay Sonawane ,  Samuel Harry Ingbar

IPC: G06F17/00 ,  G06F40/30 ,  G10L15/18 ,  G10L15/22

Abstract: Techniques for evaluating a natural language understanding (NLU) component and determining an action to resolve an issue processing a user input are described. The system determines which component is invoked by a baseline NLU component is processing the user input, and which component is invoked by an updated NLU component. Based on that information, the system selects the action to resolve the updated NLU component generating an undesired response to the user input.

公开(公告)号：US20230142272A1

公开(公告)日：2023-05-11

申请号：US17973674

申请日：2022-10-26

Applicant: Amazon Technologies, Inc.

Inventor： Pavel Bhowmik ,  Melanie C B Gens ,  Sachin Midha ,  Rahul Gupta ,  Sriram Venkatapathy ,  Xinhong Zhang ,  Anoop Kumar ,  Pooja Sanjay Sonawane ,  Samuel Harry Ingbar

IPC: G06F40/30 ,  G10L15/18

CPC classification number: G06F40/30 ,  G10L15/1822 ,  G10L2015/223

Abstract: Techniques for evaluating a natural language understanding (NLU) component and determining an action to resolve an issue processing a user input are described. The system determines which component is invoked by a baseline NLU component is processing the user input, and which component is invoked by an updated NLU component. Based on that information, the system selects the action to resolve the updated NLU component generating an undesired response to the user input.

公开(公告)号：US11574637B1

公开(公告)日：2023-02-07

申请号：US17014042

申请日：2020-09-08

Applicant: Amazon Technologies, Inc.

Inventor： Anoop Kumar ,  Anil K Ramakrishna ,  Sriram Venkatapathy ,  Rahul Gupta ,  Sankaranarayanan Ananthakrishnan ,  Premkumar Natarajan

IPC: G10L15/30 ,  G10L15/22 ,  G10L13/02 ,  G06N20/20

Abstract: Techniques for using a federated learning framework to update machine learning models for spoken language understanding (SLU) system are described. The system determines which labeled data is needed to update the models based on the models generating an undesired response to an input. The system identifies users to solicit labeled data from, and sends a request to a user device to speak an input. The device generates labeled data using the spoken input, and updates the on-device models using the spoken input and the labeled data. The updated model data is provided to the system to enable the system to update the system-level (global) models.

公开(公告)号：US11507752B1

公开(公告)日：2022-11-22

申请号：US17002862

申请日：2020-08-26

Applicant: Amazon Technologies, Inc.

Inventor： Pavel Bhowmik ,  Melanie C B Gens ,  Sachin Midha ,  Rahul Gupta ,  Sriram Venkatapathy ,  Xinhong Zhang ,  Anoop Kumar ,  Pooja Sanjay Sonawane ,  Samuel Harry Ingbar

IPC: G06F17/00 ,  G06F40/30 ,  G10L15/18 ,  G10L15/22

Abstract: Techniques for evaluating a natural language understanding (NLU) component and determining an action to resolve an issue processing a user input are described. The system determines which component is invoked by a baseline NLU component is processing the user input, and which component is invoked by an updated NLU component. Based on that information, the system selects the action to resolve the updated NLU component generating an undesired response to the user input.