公开(公告)号：US11929070B1

公开(公告)日：2024-03-12

申请号：US17461124

申请日：2021-08-30

Applicant: Amazon Technologies, Inc.

Inventor： Ruhi Sarikaya ,  Zheng Du ,  Xiaohu Liu ,  Kai Liu ,  Sriharsha Venkata Chintalapati ,  Chenlei Guo ,  Hung Tuan Pham ,  Joe Pemberton ,  Zhenyu Yao ,  Bigyan Rajbhandari

IPC: G10L15/22 ,  G06N20/20 ,  G10L15/02 ,  G10L15/06

CPC classification number: G10L15/22 ,  G06N20/20 ,  G10L15/02 ,  G10L15/063 ,  G10L2015/225

Abstract: Techniques for performing centralized unsuperivised learning in a multi-domain system are described. A user may request labeled data for an ML task, where the request includes a prompt for obtaining relevant explicit user feedback. The system may use the prompt to collect explicit user feedback for relevant runtime user inputs. After a duration of time (in the user's request for labeled data) has elapsed, the system determines whether collected user feedback indicates processing of the user input was defective and, if so, determines a cause of the defective processing. The system then uses one or more label generators to generate labeled data using the collected user feedback, whether the processing was defective, and the determined defect cause.

公开(公告)号：US20240347050A1

公开(公告)日：2024-10-17

申请号：US18663237

申请日：2024-05-14

Applicant: Amazon Technologies, Inc.

Inventor： Ruhi Sarikaya ,  Hung Tuan Pham ,  Savas Parastatidis ,  Dean Curtis ,  Pushpendre Rastogi ,  Nitin Ashok Jain ,  John Arland Nave ,  Abhinav Sethy ,  Arpit Gupta ,  Mayank Kumar ,  Nakul Dahiwade ,  Arshdeep Singh ,  Nikhil Reddy Kortha ,  Rohit Prasad

IPC: G10L15/16 ,  G06F16/9032 ,  G10L13/08

CPC classification number: G10L15/16 ,  G06F16/90332 ,  G10L13/08

Abstract: Techniques for recommending a skill experience to a user after a user-system dialog session has ended are described. Upon a dialog session ending, the system uses a first machine learning model to determine potential intents to recommend to a user. The system then uses a second machine learning model to determine a particular skill and intent to recommend. The system then prompts the user to accept the recommended skill and intent. If the user accepts, the system calls the recommended skill to execute. As part of calling the skill, the system sends to the skill at least one entity provided in a natural language user input of the ended dialog session. This enables the skill to skip welcome prompts, and initiate processing to output a response based on the intent and the at least one entity of the ended dialog session.

公开(公告)号：US11544504B1

公开(公告)日：2023-01-03

申请号：US17022883

申请日：2020-09-16

Applicant: Amazon Technologies, Inc.

Inventor： Xing Fan ,  Hung Tuan Pham ,  Chenlei Guo ,  Xiaohu Liu ,  Shuting Tang

IPC: G06K9/62 ,  G06F16/9032 ,  G06F40/35

Abstract: Techniques for determining an intent of a subsequent user input in a dialog are described. The system processes historic interaction data that is structured based on natural language understanding (NLU) hypotheses, with each NLU hypothesis being associated with one or more past user inputs received by the system, one or more sample inputs, and one or more past system responses. Based on processing of the historic interaction data and dialog data of previous turns of the dialog, the system determines candidate intents for the subsequent turn of the dialog. The system also uses context data to determine the candidate intents.

公开(公告)号：US11527237B1

公开(公告)日：2022-12-13

申请号：US17024959

申请日：2020-09-18

Applicant: Amazon Technologies, Inc.

Inventor： Ruhi Sarikaya ,  Hung Tuan Pham ,  Savas Parastatidis ,  Dean Curtis ,  Pushpendre Rastogi ,  Nitin Ashok Jain ,  John Arland Nave ,  Abhinav Sethy ,  Arpit Gupta ,  Mayank Kumar ,  Nakul Dahiwade ,  Arshdeep Singh ,  Nikhil Reddy Kortha ,  Rohit Prasad

IPC: G10L13/00 ,  G10L15/16 ,  G06F16/9032 ,  G10L13/08

Abstract: Techniques for recommending a skill experience to a user after a user-system dialog session has ended are described. Upon a dialog session ending, the system uses a first machine learning model to determine potential intents to recommend to a user. The system then uses a second machine learning model to determine a particular skill and intent to recommend. The system then prompts the user to accept the recommended skill and intent. If the user accepts, the system calls the recommended skill to execute. As part of calling the skill, the system sends to the skill at least one entity provided in a natural language user input of the ended dialog session. This enables the skill to skip welcome prompts, and initiate processing to output a response based on the intent and the at least one entity of the ended dialog session.

公开(公告)号：US11990122B2

公开(公告)日：2024-05-21

申请号：US18076987

申请日：2022-12-07

Applicant: Amazon Technologies, Inc.

Inventor： Ruhi Sarikaya ,  Hung Tuan Pham ,  Savas Parastatidis ,  Dean Curtis ,  Pushpendre Rastogi ,  Nitin Ashok Jain ,  John Arland Nave ,  Abhinav Sethy ,  Arpit Gupta ,  Mayank Kumar ,  Nakul Dahiwade ,  Arshdeep Singh ,  Nikhil Reddy Kortha ,  Rohit Prasad

IPC: G10L15/26 ,  G06F16/9032 ,  G10L13/08 ,  G10L15/16

CPC classification number: G10L15/16 ,  G06F16/90332 ,  G10L13/08

Abstract: Techniques for recommending a skill experience to a user after a user-system dialog session has ended are described. Upon a dialog session ending, the system uses a first machine learning model to determine potential intents to recommend to a user. The system then uses a second machine learning model to determine a particular skill and intent to recommend. The system then prompts the user to accept the recommended skill and intent. If the user accepts, the system calls the recommended skill to execute. As part of calling the skill, the system sends to the skill at least one entity provided in a natural language user input of the ended dialog session. This enables the skill to skip welcome prompts, and initiate processing to output a response based on the intent and the at least one entity of the ended dialog session.

公开(公告)号：US20230215425A1

公开(公告)日：2023-07-06

申请号：US18076987

申请日：2022-12-07

Applicant: Amazon Technologies, Inc.

Inventor： Ruhi Sarikaya ,  Hung Tuan Pham ,  Savas Parastatidis ,  Dean Curtis ,  Pushpendre Rastogi ,  Nitin Ashok Jain ,  John Arland Nave ,  Abhinav Sethy ,  Arpit Gupta ,  Mayank Kumar ,  Nakul Dahiwade ,  Arshdeep Singh ,  Nikhil Reddy Kortha ,  Rohit Prasad

IPC: G10L15/16 ,  G06F16/9032 ,  G10L13/08

CPC classification number: G10L15/16 ,  G06F16/90332 ,  G10L13/08

Abstract: Techniques for recommending a skill experience to a user after a user-system dialog session has ended are described. Upon a dialog session ending, the system uses a first machine learning model to determine potential intents to recommend to a user. The system then uses a second machine learning model to determine a particular skill and intent to recommend. The system then prompts the user to accept the recommended skill and intent. If the user accepts, the system calls the recommended skill to execute. As part of calling the skill, the system sends to the skill at least one entity provided in a natural language user input of the ended dialog session. This enables the skill to skip welcome prompts, and initiate processing to output a response based on the intent and the at least one entity of the ended dialog session.