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公开(公告)号：US20230089285A1
公开(公告)日：2023-03-23
申请号：US17853013
申请日：2022-06-29
Applicant: Amazon Technologies, Inc.
Inventor： Xing Fan , Zheng Chen , Yuan Ling , Lambert Leo Mathias , Chenlei Guo
IPC: G10L15/197 , G10L15/22 , G10L15/30 , G10L15/18
Abstract: A system is provided for reducing friction during user interactions with a natural language processing system, such as voice assistant systems. The system determines a pre-trained model using dialog session data corresponding to multiple user profiles. The system determines a fine-tuned model using the pre-trained model and a fine-tuning dataset that corresponds to a particular task, such as query rewriting. The system uses the fine-tuned model to process a user input and determine an alternative representation of the input that can result in a desired response from the natural language processing system.
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公开(公告)号：US11386890B1
公开(公告)日：2022-07-12
申请号：US16788085
申请日：2020-02-11
Applicant: Amazon Technologies, Inc.
Inventor： Xing Fan , Zheng Chen , Yuan Ling , Lambert Leo Mathias , Chenlei Guo
IPC: G10L15/197 , G10L15/22 , G10L15/30 , G10L15/18
Abstract: A system is provided for reducing friction during user interactions with a natural language processing system, such as voice assistant systems. The system determines a pre-trained model using dialog session data corresponding to multiple user profiles. The system determines a fine-tuned model using the pre-trained model and a fine-tuning dataset that corresponds to a particular task, such as query rewriting. The system uses the fine-tuned model to process a user input and determine an alternative representation of the input that can result in a desired response from the natural language processing system.
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公开(公告)号：US11380304B1
公开(公告)日：2022-07-05
申请号：US16363880
申请日：2019-03-25
Applicant: Amazon Technologies, Inc.
Inventor： Pragaash Ponnusamy , Alireza Roshan Ghias , Chenlei Guo
IPC: G06F40/00 , G10L15/18 , G10L15/06 , G10L15/26 , G06F40/35 , G10L15/19 , G10L15/22 , G10L15/183 , G06F40/30
Abstract: A system is provided for handling errors during automatic speech recognition by processing a potentially defective utterance to determine an alternative, potentially successful utterance. The system processes an ASR hypothesis, using a probabilistic graph, to determine a likelihood that it will result in an error. Using the probabilistic graph, the system determines an alternate utterance.
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公开(公告)号：US12254867B2
公开(公告)日：2025-03-18
申请号：US17856090
申请日：2022-07-01
Applicant: Amazon Technologies, Inc.
Inventor： Chenlei Guo , Xing Fan , Chengyuan Ma , Shuting Tang , Kai Wei
Abstract: A system is provided for a self-learning policy engine that can be used by various spoken language understanding (SLU) processing components. The system also provides for sharing contextual information from processing performed by an upstream SLU component to a downstream SLU component to facilitate decision making by the downstream SLU component. The system also provides for a SLU component to select from a variety of actions to take. A SLU component may implement an instance of the self-learning policy that is specifically configured for the particular SLU component.
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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.
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Patent Agency Ranking
公开(公告)号：US11437027B1
公开(公告)日：2022-09-06
申请号：US16703609
申请日：2019-12-04
Applicant: Amazon Technologies, Inc.
Inventor： Chenlei Guo , Xing Fan , Jin Hock Ong , Kai Wei
IPC: G10L15/197 , G10L15/22 , G10L15/18 , G10L15/30
Abstract: Techniques for handling errors during processing of natural language inputs are described. A system may process a natural language input to generate an ASR hypothesis or NLU hypothesis. The system may use more than one data searching technique (e.g., deep neural network searching, convolutional neural network searching, etc.) to generate an alternate ASR hypothesis or NLU hypothesis, depending on the type of hypothesis input for alternate hypothesis processing.
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公开(公告)号：US11151986B1
公开(公告)日：2021-10-19
申请号：US16138447
申请日：2018-09-21
Applicant: Amazon Technologies, Inc.
Inventor： Bigyan Rajbhandari , Praveen Kumar Bodigutla , Zhenxiang Zhou , Karen Catelyn Stabile , Chenlei Guo , Abhinav Sethy , Alireza Roshan Ghias , Pragaash Ponnusamy , Kevin Quinn
Abstract: Techniques for decreasing (or eliminating) the possibility of a skill performing an action that is not responsive to a corresponding user input are described. A system may train one or more machine learning models with respect to user inputs, which resulted in incorrect actions being performed by skills, and corresponding user inputs, which resulted in the correct action being performed. The system may use the trained machine learning model(s) to rewrite user inputs that, if not rewritten, may result in incorrect actions being performed. The system may implement the trained machine learning model(s) with respect to ASR output text data to determine if the ASR output text data corresponds (or substantially corresponds) to previous ASR output text data that resulted in an incorrect action being performed. If the trained machine learning model(s) indicates the present ASR output text data corresponds (or substantially corresponds) to such previous ASR output text data, the system may rewrite the present ASR output text data to correspond to text data representing a rephrase of the user input that will (or is more likely to) result in a correct action being performed.
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公开(公告)号：US11908452B1
公开(公告)日：2024-02-20
申请号：US17325523
申请日：2021-05-20
Applicant: Amazon Technologies, Inc.
Inventor： Sixing Lu , Chengyuan Ma , Chenlei Guo , Fangfu Li
CPC classification number: G10L15/01 , G06F40/30 , G10L15/005
Abstract: Techniques for presenting an alternative input representation to a user for testing and collecting processing data are described. A system may determine that a received spoken input triggers an alternative input representation for presenting. The system may output data corresponding to the alternative input representation in response to the received spoken input, and the system may receive user feedback from the user. The system may store the user feedback and processing data corresponding to processing of the alternative input representation, which may be later used to update an alternative input component configured to determine alternative input representations for spoken inputs.
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公开(公告)号：US20230047811A1
公开(公告)日：2023-02-16
申请号：US17856090
申请日：2022-07-01
Applicant: Amazon Technologies, Inc.
Inventor： Chenlei Guo , Xing Fan , Chengyuan Ma , Shuting Tang , Kai Wei
Abstract: A system is provided for a self-learning policy engine that can be used by various spoken language understanding (SLU) processing components. The system also provides for sharing contextual information from processing performed by an upstream SLU component to a downstream SLU component to facilitate decision making by the downstream SLU component. The system also provides for a SLU component to select from a variety of actions to take. A SLU component may implement an instance of the self-learning policy that is specifically configured for the particular SLU component.
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公开(公告)号：US11508361B2
公开(公告)日：2022-11-22
申请号：US16889420
申请日：2020-06-01
Applicant: Amazon Technologies, Inc.
Inventor： Isaac Joseph Madwed , Julia Kennedy Nemer , Joo-Kyung Kim , Nikko Strom , Steven Mack Saunders , Laura Maggia Panfili , Anna Caitlin Jentoft , Sungjin Lee , David Thomas , Young-Bum Kim , Pablo Cesar Ganga , Chenlei Guo , Shuting Tang , Zhenyu Yao
Abstract: Described herein is a system for responding to a frustrated user with a response determined based on spoken language understanding (SLU) processing of a user input. The system detects user frustration and responds to a repeated user input by confirming an action to be performed or presenting an alternative action, instead of performing the action responsive to the user input. The system also detects poor audio quality of the captured user input, and responds by requesting the user to repeat the user input. The system processes sentiment data and signal quality data to respond to user inputs.
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