Amazon Technologies, Inc.

Aishwarya Naresh Reganti

Govindarajan Sundaram Thattai

Dilek Zeynep Hakkani-Tur

Gokhan Tur

Rohit Prasad

Arindam Mandal

Amitabh Saikia

Prakash Krishnan

Tagyoung Chung

Premkumar Natarajan

Raefer Christopher Gabriel

Joel Joseph Chengottusseriyil

Qing Ping

Feiyang Niu

Qiaozi Gao

Chien-wei Lin

Devesh Mohan Pandey

Prashanth Rajagopal

Meyyappan Sundaram

Shanchan Wu

Techniques for facilitating natural language interactions with visual interactive content are described. During a build time, a system analyzes various websites and applications relating to a particular user goal to understand website and application navigation and information relating to the user goal. The learned information is used to store configuration data. During runtime, when a user request performance of an action, the system engages in a dialog with the user to complete the user's goal. The system uses the stored configuration data to determine actions to be performed at a website or application to complete the user's goal, and determines system responses to present to the user to facilitate completion of the goal. Such system responses may request information from the user, may inform the user of information displayed at the website or application, etc.

Natural language interactions with interactive visual content

Devices and techniques are generally described for learning personalized concepts for natural language processing. In various examples, a first natural language input may be received. In some examples, a determination may be made that the first natural language input comprises non-actionable slot data. A dialog session may be initiated with the user. In some examples, first slot data that is indicated by the user during the dialog session may be determined. In various examples, data representing the first slot data may be stored in a database in association with the first natural language input.

Natural language processing

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San Jose, CA, United States of America

Aishwarya Naresh Reganti