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We present an approach to dialogue management and interpretation that evaluates and selects amongst candidate dialogue moves based on features at multiple levels. Multiple interpretation methods can be combined, multiple speech recognition and parsing hypotheses tested, and multiple candidate dialogue moves considered to choose the highest scoring(More)
In the past few years, we have been developing a robust, wide-coverage, and cogni-tive load-sensitive spoken dialog interface, CHAT (Conversational Helper for Automotive Tasks). New progress has been made to address issues related to dynamic and attention-demanding environments, such as driving. Specifically, we try to address imperfect input and imperfect(More)
Spoken dialogue interfaces, mostly command-and-control, become more visible in applications where attention needs to be shared with other tasks, such as driving a car. The deployment of the simple dialog systems, instead of more sophisticated ones, is partly because the computing platforms used for such tasks have been less powerful and partly because(More)
We present an approach to multi-device dialogue that evaluates and selects amongst candidate dialogue moves based on features at multiple levels. Multiple sources of information can be combined, multiple speech recognition and parsing hypotheses tested, and multiple devices and moves considered to choose the highest scoring hypothesis overall. The approach(More)
In this demonstration we present a conversational dialog system for automobile drivers. The system provides a voice-based interface to playing music, finding restaurants, and navigating while driving. The design of the system as well as the new technologies developed will be presented. Our evaluation showed that the system is promising, achieving high task(More)
1. Abstract This paper describes an approach for selecting the best candidate dialogue move in multi-device dialogue systems based on multiple sources of information, including parsing hypotheses, contextual information, information from topic classifiers and semantic features. At the basis of this approach stands the ability to reorder n-best lists of(More)
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