Amazon Technologies, Inc.

Di Jin

Dilek Zeynep Hakkani-Tur

Yang Liu

Behnam Hedayatnia

Spandana Gella

Seokhwan Kim

Sungjin Lee

Dilek Hakkani-Tür

Devamanyu Hazarika

Mahdi Namazifar

Chao Zhao

Alexandros Papangelis

Prakhar Gupta

Sijia Liu

Julia Bell Hirschberg

Patrick Lueder Lange

A dialog management system that coordinates system dialog responses based on natural language guidelines which provide non-deterministic ways for the system to properly respond to a dialog input based on the dialog history/context. For each input, an appropriate guideline is selected by a machine learning component based on the dialog history. The guideline is then sent, along with the dialog history, to a downstream machine learning component to determine an appropriate dialog system response.

Virtual assistant dialog management

Techniques for generating a natural language response to a user input of a dialog are described. A system receives a natural language user input of a dialog and determines dialog history data including a previous natural language user input of the dialog. Based on the first natural language user input and the dialog history data, the system generates at least a first question associated with the natural language user input. Based on the first natural language user input and the dialog history data, the system generates at least a first answer to the at least first question. Using the dialog history data, the first natural language question, and the first natural language answer, the system generates an output responsive to the natural language user input.

Natural language response generation

Techniques for generating opinion-based content responsive to a user input are described. The system may receive a user input, and determine dialog context data corresponding to a dialog between a user and the system, and including the user input. The system may determine generation of content responsive to the user input requires opinion-based knowledge, and may extract entities from the dialog context data, and determine natural language data of a knowledge base that includes entities similar to the extracted entities. The system may processes the natural language data and the dialog context data to determine a subset of the natural language data that is responsive to the user input. The system may generate output data responsive to the user input using the responsive natural language data and the dialog context.

Opinion-based natural language response generation

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Santa Clara, CA, United States of America

Di Jin