Amazon Technologies, Inc.

Nikhil Reddy Kortha

Ruhi Sarikaya

Rohit Prasad

Arpit Gupta

Abhinav Sethy

Savas Parastatidis

Pushpendre Rastogi

Nitin Ashok Jain

John Arland Nave

Mayank Kumar

Nakul Dahiwade

Arshdeep Singh

Dean Curtis

Hung The Pham

Hung Tuan Pham

Techniques for recommending a skill experience to a user after a user-system dialog session has ended are described. Upon a dialog session ending, the system uses a first machine learning model to determine potential intents to recommend to a user. The system then uses a second machine learning model to determine a particular skill and intent to recommend. The system then prompts the user to accept the recommended skill and intent. If the user accepts, the system calls the recommended skill to execute. As part of calling the skill, the system sends to the skill at least one entity provided in a natural language user input of the ended dialog session. This enables the skill to skip welcome prompts, and initiate processing to output a response based on the intent and the at least one entity of the ended dialog session.

User-system dialog expansion

Growing community of inventors

Seattle, WA, United States of America

Nikhil Reddy Kortha