Amazon Technologies, Inc.

Shuting Tang

Chenlei Guo

Xing Fan

Kai Wei

Chengyuan Ma

Xiaohu Liu

Nikko Strom

Young-Bum Kim

David Robert Thomas

Hung The Pham

Isaac Joseph Madwed

Julia Kennedy Nemer

Sungjin Lee

Steven Mack Saunders

Zhenyu Yao

Pablo Cesar Ganga

Joo-Kyung Kim

Laura Maggia Panfili

Anna Caitlin Jentoft

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.

Spoken language understanding system

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.

Dialog management system

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.

Sentiment aware voice user interface

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Seattle, WA, United States of America

Shuting Tang