tailieunhanh - Báo cáo khoa học: "Setting Up User Action Probabilities in User Simulations for Dialog System Development"

User simulations are shown to be useful in spoken dialog system development. Since most current user simulations deploy probability models to mimic human user behaviors, how to set up user action probabilities in these models is a key problem to solve. One generally used approach is to estimate these probabilities from human user data. However, when building a new dialog system, usually no data or only a small amount of data is available. | Setting Up User Action Probabilities in User Simulations for Dialog System Development Hua Ai University of Pittsburgh Pittsburgh Pa 15260 UsA hua@ Diane Litman University of Pittsburgh Pittsburgh Pa 15260 UsA litman@ Abstract User simulations are shown to be useful in spoken dialog system development. Since most current user simulations deploy probability models to mimic human user behaviors how to set up user action probabilities in these models is a key problem to solve. One generally used approach is to estimate these probabilities from human user data. However when building a new dialog system usually no data or only a small amount of data is available. In this study we compare estimating user probabilities from a small user data set versus handcrafting the probabilities. We discuss the pros and cons of both solutions for different dialog system development tasks. 1 Introduction User simulations are widely used in spoken dialog system development. Recent studies use user simulations to generate training corpora to learn dialog strategies automatically Williams and Young 2007 Lemon and Liu 2007 or to evaluate dialog system performance Lopez-Cozar et al. 2003 . Most studies show that using user simulations significantly improves dialog system performance as well as speeds up system development. since user simulation is such a useful tool dialog system researchers have studied how to build user simulations from a variety of perspectives. Some studies look into the impact of training data on user simulations. For example Georgila et al. 2008 observe differences between simulated users trained from human users of different age groups. Other studies explore different simulation models . the mechanism of deciding the next user actions given the current dialog context. Schatzmann et al. 2006 give a thorough review of different types of simulation models. Since most of these current user simulation techniques use probabilistic models to .