Persistent Information State in a Data-Centric Architecture
نویسندگان
چکیده
We present the ADAMACH data centric dialog system, that allows to perform onand offline mining of dialog context, speech recognition results and other system-generated representations, both within and across dialogs. The architecture implements a “fat pipeline” for speech and language processing. We detail how the approach integrates domain knowledge and evolving empirical data, based on a user study in the University Helpdesk domain.
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تاریخ انتشار 2008