公开(公告)号：US12154558B1

公开(公告)日：2024-11-26

申请号：US16902369

申请日：2020-06-16

Applicant: Amazon Technologies, Inc.

Inventor： Haoyu Wang ,  Albert J Morello ,  James J Logan ,  Ashish Kumar Agrawal

IPC: G10L15/187 ,  G06F40/284 ,  G06F40/295 ,  G10L15/02 ,  G10L15/26

Abstract: This disclosure proposes systems and methods for entity resolution using speech recognition data. The system can receive audio data representing an utterance and perform automatic speech recognition (ASR) processing on the audio data to generate at least a first ASR data and a second ASR data. The system can perform natural language understanding (NLU) processing on the first ASR data to determine intent data and an indication of an entity. The system can determine a first portion of the first ASR data that corresponds to the indication of the entity. The system can determine a second portion of the second ASR data that corresponds to the indication of the entity without performing NLU on the second ASR data. The system can perform entity resolution (ER) on the second portion to identify a first entity.

公开(公告)号：US20230074681A1

公开(公告)日：2023-03-09

申请号：US17866965

申请日：2022-07-18

Applicant: Amazon Technologies, Inc.

Inventor： Han Wang ,  Tong Wang ,  Yue Liu ,  Ashish Kumar Agrawal

IPC: G10L15/18 ,  G10L15/26

Abstract: Techniques for processing complex natural language inputs are described. A complex natural language input may be semantically tagged and parsed to identify individual clauses in the complex natural language input. An execution graph may be generated to represent the clauses and their dependencies. Nodes of the execution graph may be processed using NLU processing and/or a knowledge graph or other information storage and retrieval techniques, and results of such processing may be used to update clause variables with specific entities in the execution graph.

公开(公告)号：US11908463B1

公开(公告)日：2024-02-20

申请号：US17361761

申请日：2021-06-29

Applicant: Amazon Technologies, Inc.

Inventor： Arjit Biswas ,  Shishir Bharathi ,  Anushree Venkatesh ,  Yun Lei ,  Ashish Kumar Agrawal ,  Siddhartha Reddy Jonnalagadda ,  Prakash Krishnan ,  Arindam Mandal ,  Raefer Christopher Gabriel ,  Abhay Kumar Jha ,  David Chi-Wai Tang ,  Savas Parastatidis

IPC: G10L15/22 ,  G06F40/35 ,  G10L15/183 ,  G10L15/18 ,  G06F40/279 ,  G06F40/295 ,  G10L15/19 ,  G06F40/30

CPC classification number: G10L15/183 ,  G06F40/279 ,  G10L15/1815 ,  G10L15/22 ,  G06F40/295 ,  G06F40/30 ,  G06F40/35 ,  G10L15/1822 ,  G10L15/19 ,  G10L2015/228

Abstract: Techniques for storing and using multi-session context are described. A system may store context data corresponding to a first interaction, where the context data may include action data, entity data and a profile identifier for a user. Later the stored context data may be retrieved during a second interaction corresponding to the entity of the second interaction. The second interaction may take place at a system different than the first interaction. The system may generate a response during the second interaction using the stored context data of the prior interaction.

公开(公告)号：US11804225B1

公开(公告)日：2023-10-31

申请号：US17375458

申请日：2021-07-14

Applicant: Amazon Technologies, Inc.

Inventor： Ashish Kumar Agrawal ,  Kemal Oral Cansizlar ,  Suranjit Adhikari ,  Shucheng Zhu ,  Raefer Christopher Gabriel ,  Arindam Mandal

IPC: G10L15/22 ,  G10L15/18 ,  G10L15/30

CPC classification number: G10L15/22 ,  G10L15/1815 ,  G10L15/30 ,  G10L2015/223

Abstract: Techniques for conversation recovery in a dialog management system are described. A system may determine, using dialog models, that a predicted action to be performed by a skill component is likely to result in an undesired response or that the skill component is unable to respond to a user input of a dialog session. Rather than informing the user that the skill component is unable to respond, the system may send data to the skill component to enable the skill component to determine a correct action responsive to the user input. The data may include an indication of the predicted action and/or entity data corresponding to the user input. The system may receive, from the skill component, response data corresponding to the user input, and may use the response data to update a dialog context for the dialog session and an inference engine of the dialog management system.

公开(公告)号：US20240185846A1

公开(公告)日：2024-06-06

申请号：US18439166

申请日：2024-02-12

Applicant: Amazon Technologies, Inc.

Inventor： Arjit Biswas ,  Shishir Bharathi ,  Anushree Venkatesh ,  Yun Lei ,  Ashish Kumar Agrawal ,  Siddhartha Reddy Jonnalagadda ,  Prakash Krishnan ,  Arindam Mandal ,  Raefer Christopher Gabriel ,  Abhay Kumar Jha ,  David Chi-Wai Tang ,  Savas Parastatidis

IPC: G10L15/183 ,  G06F40/279 ,  G06F40/295 ,  G06F40/30 ,  G06F40/35 ,  G10L15/18 ,  G10L15/19 ,  G10L15/22

CPC classification number: G10L15/183 ,  G06F40/279 ,  G10L15/1815 ,  G10L15/22 ,  G06F40/295 ,  G06F40/30 ,  G06F40/35 ,  G10L15/1822 ,  G10L15/19 ,  G10L2015/228

Abstract: Techniques for storing and using multi-session context are described. A system may store context data corresponding to a first interaction, where the context data may include action data, entity data and a profile identifier for a user. Later the stored context data may be retrieved during a second interaction corresponding to the entity of the second interaction. The second interaction may take place at a system different than the first interaction. The system may generate a response during the second interaction using the stored context data of the prior interaction.