MEASURING THE DIFFERENCES BETWEEN HUMAN-HUMAN AND HUMAN-MACHINE DIALOGS

In this paper, we assess the applicability of user simulation techniques to generate dialogs which are similar to real human-machine spoken interactions.
To do so, we present the results of the comparison between three corpora acquired by means of different techniques. The first corpus was acquired with real users.
A statistical user simulation technique has been applied to the same task to acquire the second corpus. In this technique, the next user answer is selected by means of a classification process that takes into account the previous dialog history, the lexical information in the clause, and the subtask of the dialog to which it contributes. Finally, a dialog simulation technique has been developed for the acquisition of the third corpus. This technique uses a random selection of the user and system turns, defining stop conditions for automatically deciding if the simulated dialog is successful or not. We use several evaluation measures proposed in previous research to compare between our three acquired corpora, and then discuss the similarities and differences with regard to these measures.