Sri International

James F Carpenter

Girish Acharya

Edgar Kalns

Min Yin

Michael Wessel

Hyong-Gyun Kim

Ajay Divakaran

William Scott Mark

Kenneth C Nitz

Elizabeth E Shriberg

Amir Tamrakar

Dimitra Vergyri

Michael Frandsen

Andreas Kathol

Cory Albright

Jihua Huang

Andreas Tsiartas

Aaron Spaulding

Eric Law

Greg Ho

Brent Mombourquette

Leonor Almada

Roland Heusser

David Salter

Nikoletta Basiou

A conversational assistant for conversational engagement platform can contain various modules including a user-model augmentation module, a dialogue management module, and a user-state analysis input/output module. The dialogue management module receives metrics tied to a user from the other modules to understand a current topic and a user's emotions regarding the current topic from the user-state analysis input/output module and then adapts dialogue from the dialogue management module to the user based on dialogue rules factoring in these different metrics. The dialogue rules also factors in both i) a duration of a conversational engagement with the user and ii) an attempt to maintain a positive experience for the user with the conversational engagement. A flexible ontology relationship representation about the user is built and stores learned metrics about the user over time with each conversational engagement, and then in combination with the dialogue rules, drives the conversations with the user.

Conversational assistant for conversational engagement

Methods, computing devices, and computer-program products are provided for implementing a virtual personal assistant. In various implementations, a virtual personal assistant can be configured to receive sensory input, including at least two different types of information. The virtual personal assistant can further be configured to determine semantic information from the sensory input, and to identify a context-specific framework. The virtual personal assistant can further be configured to determine a current intent. Determining the current intent can include using the semantic information and the context-specific framework. The virtual personal assistant can further be configured to determine a current input state. Determining the current input state can include using the semantic information and one or more behavioral models. The behavioral models can include one or more interpretations of previously-provided semantic information. The virtual personal assistant can further be configured to determine an action using the current intent and the current input state.

VPA with integrated object recognition and facial expression recognition

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Mountain View, CA, United States of America

James F Carpenter