Year: 2007
Type: article
Abstract: Current dialogue systems generally operate in a pipelined, modular fashion on one complete utterance at a time.Evidence from human language understanding shows that human understanding operates incrementally and makes use of multiple sources of information during the parsing process, including traditionally "later" components such as pragmatics.In this paper we describe a spoken dialogue system that understands language incrementally, provides visual feedback on possible referents during the course of the user's utterance, and allows for overlapping speech and actions.We further present findings from an empirical study showing that the resulting dialogue system is faster overall than its nonincremental counterpart.Furthermore, the incremental system is preferred to its nonincremental counterpartbeyond what is accounted for by factors such as speed and accuracy.These results indicate that successful incremental understanding systems will improve both performance and usability.
Institutions: Arizona State University, University of Rochester
Language: English
Topic: Speech and dialogue systems
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2766929078