Carnegie Mellon University

Anthony Slavko Tomasic

John Doyle Zimmerman

Ian Hargraves

Cassondra Eng

Erik Thiessen

Amy Ogan

A system for interactive system using speech recognition and digital media is described. The system uses automated speech recognition and recognizes interactions from users to execute digital media items. The interactions are based on behavior of the user. The user is given a prompt. If the student responds to a prompt correctly, the student is rewarded with an animation. Otherwise the user experience continues without a reward. The system recognizes natural language responses for interactions of the user. The media item is dynamically generated as the user interacts with the digital media item.

Interactive system using speech recognition and digital media

In various embodiments, a method for processing a user request is provided. The method may include receiving input data from a user including at least natural language associated with a user request; analyzing the user input data with an intermediary agent; selecting at least one form based on analyzing the user input data; and, executing at least one update based on at least one form.

Intent-based information processing and updates

Mixed-initiative message-augmenting agent systems and methods that provide users with tools that allow them to respond to messages, such as email messages, containing requests for information or otherwise requiring responses that require information that needs to be retrieved from one or more data sources. The systems and methods allow users to train machine-learning agents how to retrieve and present information in responses to like messages so that the machine-learning agents can eventually automatedly generate responses with minimal involvement by the users. Embodiments of the systems and methods allow users to build message-augmenting forms containing the desired information for responding to messages and to demonstrate to the machine-learning agents where to retrieve pertinent information for populating the forms. Embodiments of the systems and methods allow users to modify and repair automatically generated forms to continually improve the knowledge of the machine-learning agents.

Systems and methods for implementing a machine-learning agent to retrieve information in response to a message

In various embodiments, a method for processing a request made by a requester is provided. The method may include receiving at least one request from at least one requester, the request being in the form of natural language; analyzing the request with an agent; selecting at least one form based on analyzing the request; permitting a service agent to perform at least one step in association with the request; executing at least one update based on at least one form; and, forwarding information regarding processing of the request to a learning module operatively associated with the agent.

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Pittsburgh, PA, United States of America

Anthony Slavko Tomasic