Sri International

Edgar Kalns

William Scott Mark

Necip Fazil Ayan

Girish Acharya

James R Carpenter

Min Yin

Michael Wessel

Hyong-Gyun Kim

Ajay Divakaran

Kenneth C Nitz

Elizabeth E Shriberg

Michael John Wolverton

Amir Tamrakar

Douglas A Bercow

Dayne B Freitag

Michael Frandsen

Thomas J Lee

Jihua Huang

Cory Albright

Andreas Tsiartas

Eric Law

Greg Ho

James F Carpenter

Brent Mombourquette

Dimitra Vergyri

Andreas Kathol

Aaron Spaulding

David A Salter

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

A computing system is operable as virtual personal assistant (VPA) to understand relationships between different instances of natural language dialog expressed by different people in a multi-person conversational dialog session. The VPA can develop a common resource, a shared intent, which represents the VPA's semantic understanding of at least a portion of the multi-person dialog experience. The VPA can store and manipulate multiple shared intents, and can alternate between different shared intents as the multi-person conversation unfolds. With the shared intents, the computing system can generate useful action items and present the action items to one or more of the participants in the dialog session.

Sharing intents to provide virtual assistance in a multi-person dialog

A virtual personal assistant (VPA) application analyzes intents to, among other things, enhance or personalize a user's dialog experience with the VPA application. A set of intents, or multiple sets of intents, are maintained over the course of one or more user-specific dialog sessions with the VPA. Inferences may be derived from the set or sets of intents and incorporated into a current or future dialog session between the VPA and a user of the VPA application. In some embodiments, the inferences are only made available through the systemic understanding of natural language discourse by the VPA.

Using intents to analyze and personalize a user's dialog experience with a virtual personal assistant

A platform for developing a virtual personal assistant ('VPA') application includes an ontology that defines a computerized structure for representing knowledge relating to one or more domains. A domain may refer to a category of information and/or activities in relation to which the VPA application may engage in a conversational natural language dialog with a computing device user. Re-usable VPA components may be linked to or included in the ontology. An ontology populating agent may at least partially automate the process of populating the ontology with domain-specific information. The re-usable VPA components may be linked with the domain-specific information through the ontology. A VPA application created with the platform may include domain-adapted re-usable VPA components that may be called upon by an executable VPA engine to determine a likely intended meaning of conversational natural language input of the user and/or initiate an appropriate system response to the input.

Rapid development of virtual personal assistant applications

Growing community of inventors

San Jose, CA, United States of America

Edgar Kalns