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This paper analyses language modeling in spoken dialogue systems for accessing a database. The use of several language models obtained by exploiting dialogue predictions gives better results than the use of a single model for the whole dialogue interaction. For this reason several models have been created, each one for a specific system question, such as the request or the confirmation of a parameter.The use of dialogue-dependent language models increases the performance both at the recognition and at the understanding level, especially on answers to system requests. Moreover using other methods to increase performances, like automatic clustering of vocabularywords or the use of better acoustic models during recognition, does not affect the improvements given by dialogue-dependent language models.The system used in our experiments is Dialogos, the Italian spoken dialogue system used for accessing railway timetable information over the telephone. The experiments were carried out on a large corpus of dialogues collected using Dialogos.

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more com r twelve call centres are planned e of the system and for consortium was oriented tors. In this view, the human CSELT, Ferrovie rafica Varese, and Saritel. ARlSE e: SNCF, IRIT, LIMSI, VECSYS KPN, KUN in Holland; PHILIPS, All the speech technology for the Italian consortium was provided by CSELT : the speech recognizer wasFlexusB and the CSELT speech synthesiser was EloquensB.

This paper presents Dialogos, a real-time system for human-machine spoken dialogue on the telephone in task-oriented domains. The system has been tested in a large trial with inexperienced users and it has proved robust enough to allow spontaneous interactions both to users which get good recognition performance and to the ones which get lower scores. The robust behavior of the system has been achieved by combining the use of specific language models during the recognition phase of analysis, the tolerance toward spontaneous speech phenomena, the activity of a robust parser, and the use of pragmatic-based dialogue knowledge. This integration of the different modules allows to deal with partial or total breakdowns of the different levels of analysis. We report the field trial data of the system and the evaluation results of the overall system and of the submodules.