The thoughtful elephant: strategies for spoken dialog systems

We present technology used in spoken dialog systems for applications of a wide range. They include tasks from the travel domain and automatic switchboards as well as large scale directory assistance. The overall goal in developing spoken dialog systems is to allow for a natural and flexible dialog flow similar to human-human interaction. This imposes the challenging task to recognize and interpret user input, where he/she is allowed to choose from an unrestricted vocabulary and an infinite set of possible formulations. We therefore put emphasis on strategies that make the system more robust while still maintaining a high level of naturalness and flexibility. In view of this paradigm, we found that two fundamental principles characterize many of the proposed methods: to consider available sources of information as early as possible; and to keep alternative hypotheses and delay the decision for a single option as long as possible. We describe how our system architecture caters to incorporating application specific knowledge, including, for example, database constraints, in the determination of the best sentence hypothesis for a user turn. On the next higher level, we use the dialog history to assess the plausibility of a sentence hypothesis by applying consistency checks with information items from previous user turns. In particular, we demonstrate how combination decisions over several turns can be exploited to boost the recognition performance of the system