A Methodology for Learning Optimal Dialog Strategies
نویسندگان
چکیده
In this paper, we present a technique for learning new dialog strategies by using a statistical dialog manager that is trained from a dialog corpus. A dialog simulation technique has been developed to acquire data required to train the dialog model and then explore new dialog strategies. A set of measures has also been defined to evaluate the dialog strategy that is automatically learned. We have applied this technique to explore the space of possible dialog strategies for a dialog system that collects monitored data from patients suffering from diabetes.
منابع مشابه
Optimization of Dialog Strategies using Automatic Dialog Simulation and Statistical Dialog Management Techniques
In this paper, we present a technique for learning optimal dialog management strategies. An automatic dialog generation technique, including a simulation of the communication channel, has been developed to acquire the required data, train dialog models, and explore new dialog strategies in order to learn the optimal one. A set of quantitative and qualitative measures has been defined to evaluat...
متن کاملFast reinforcement learning of dialog strategies
Dialog management is a critical component of an e ective spoken language application. It is also one of the most di cult and time consuming to engineer. This paper examines the application of reinforcement learning and Markov Decision Processes (MDP's) to the problem of learning the dialog strategies. It extends work done at AT&T [1] [2] in two directions. First it examines the ability of RL to...
متن کاملA statistical approach to spoken dialog systems design and evaluation
In this paper, we present a statistical approach for the development of a dialog manager and for learning optimal dialog strategies. This methodology is based on a classification procedure that considers all of the previous history of the dialog to select the next system answer. To evaluate the performance of the dialog system, the statistical approach for dialog management has been extended to...
متن کاملEvolving optimal inspectable strategies for spoken dialogue systems
We report on a novel approach to generating strategies for spoken dialogue systems. We present a series of experiments that illustrate how an evolutionary reinforcement learning algorithm can produce strategies that are both optimal and easily inspectable by human developers. Our experimental strategies achieve a mean performance of 98.9% with respect to a predefined evaluation metric. Our appr...
متن کاملA stochastic model of human-machine interaction for learning dialog strategies
In this paper, we propose a quantitative model for dialog systems that can be used for learning the dialog strategy. We claim that the problem of dialog design can be formalized as an optimization problem with an objective function reflecting different dialog dimensions relevant for a given application. We also show that any dialog system can be formally described as a sequential decision proce...
متن کامل