Cooperative User Models in Statistical Dialog Simulators

Statistical user simulation is a promising methodology to train and evaluate the performance of (spoken) dialog systems. We work with a modular architecture for data-driven simulation where the "intentional" component of user simulation includes a User Model representing userspecific features. We train a dialog simulator that combines traits of human behavior such as cooperativeness and context with domain-related aspects via the Expectation-Maximization algorithm. We show that cooperativeness provides a finer representation of the dialog context which directly affects task completion rate.

• Type: Journal
• Year: 2010
• Where: SIGDIAL
• Authors: Meritxell González, Silvia Quarteroni, Giuseppe Riccardi, Sebastian Varges
• Keywords: Dialog, Natural Language Processing, SIGDIAL 2010, Statistical User Simulation, User Simulation