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Recent years have seen steady improvements in the quality and performance of speech-based human-machine interaction driven by a significant convergence in the methods and techniques employed. However, the quantity of training data required to improve state-of-the-art systems seems to be growing exponentially, and performance appears to be asymptoting to a level that may be inadequate for many real-world applications. This suggests that there may be a fundamental flaw in the underlying architecture of contemporary systems, as well as a failure to capitalize on the combinatorial properties of human spoken language. This paper addresses these issues and presents a novel architecture for speech-based human-machine interaction inspired by recent findings in the neurobiology of living systems. Called PRESENCE 'PREdictive SENsorimotor Control and Emulation' - this new architecture blurs the distinction between the core components of a traditional spoken language dialogue system and, instead, focuses on a recursive hierarchical feedback control structure. Cooperative and communicative behavior emerges as a by-product of an architecture that is founded on a model of interaction in which the system has in mind the needs and intentions of a user, and a user has in mind the needs and intentions of the system.
automatic speech recognition, speech synthesis, spoken language dialogue

R. Moore, "PRESENCE: A Human-Inspired Architecture for Speech-Based Human-Machine Interaction," in IEEE Transactions on Computers, vol. 56, no. , pp. 1176-1188, 2007.
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