Dialog i dramaturgia

Using Dialog-Level owledge Sources to I ecognith

We motivate and describe an implementation of the MINDS* speech recognition system. MINDS uses knowledge of dialog structures, user goals and focus in a problem solving situation. The knowledge is combined to form predictions which translate into dynamically generated semantic network grammars. An experiment evaluated recognition accuracy given different levels of knowledge as constraints. Our ...

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...

Automatic detection of task-incompleted dialog for spoken dialog system based on dialog act n-gram

In this paper, we propose a method of detecting taskincompleted users for a spoken dialog system using an N-grambased dialog history model. We collected a large amount of spoken dialog data accompanied by usability evaluation scores by users in real environments. The database was made by a field test in which naive users used a client-server music retrieval system with a spoken dialog interface...

Dialog 1971

User Modelling, Dialog Structure, And Dialog Strategy In Ham-Ans

AI dialog systems are now developing from question-answering systems toward advising systems. This includes: discussed here, but see (Jameson, Wahlster 1982). The second part o f this paper presents user modelling with respect to a dialog strategy which selects and verbalizes the appropriate speech act of recommendation. structuring dialog understanding and generating a wider range o f speech a...