Sri International

Min Yin

Girish Acharya

Edgar Kalns

Douglas E Appelt

Michael Wessel

Hyong-Gyun Kim

Ajay Divakaran

William Scott Mark

Kenneth C Nitz

Elizabeth E Shriberg

Amir Tamrakar

Michael Frandsen

Cory Albright

Jihua Huang

Andreas Tsiartas

Greg Ho

William Jarrold

Mabry W Tyson

Brent Mombourquette

James F Carpenter

Eric Law

James R Carpenter

Dimitra Vergyri

Andreas Kathol

David A Salter

Aaron Spaulding

William Mabry Tyson

Yasmina Chitti

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 non-transitory computer readable storage medium includes instructions to collect explicit feedback from a user regarding user content preferences. Multiple data sources are monitored. Topics associated with the multiple data sources are classified. The importance of the topics to the user is characterized. Content is delivered to the user when a selected topic exceeds an importance threshold for the user. Implicit feedback from the user that characterizes refined user content preferences is tracked. The instructions to characterize the importance of topics evaluates the explicit feedback and the implicit feedback.

Apparatus and method for personalized delivery of content from multiple data sources

A non-transitory computer readable storage medium includes instructions to maintain an original training set of labeled documents, where the labeled documents correspond to a variety of topics. A new labeled document corresponding to a new topic is received. The original training set of labeled documents is modulated such that the new labeled document is over-represented with respect to the original training set. This results in a modulated training set. A classifier is trained with the modulated training set to form a trained classifier.

Apparatus and method for improved classifier training

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Min Yin