Abstract
In this paper we describe Scusi?, the speech interpretation component of a spoken dialogue module designed for an autonomous robotic agent. Scusi? postulates and maintains multiple interpretations of the spoken discourse, and employs a probabilistic formalism to assess and rank hypotheses regarding the meaning of spoken utterances. These constituents in combination enable Scusi? to cope gracefully with ambiguity and speech recognition errors. The results of our evaluation are encouraging, yielding good interpretation performance for utterances of different types and lengths. © 2008 Springer Berlin Heidelberg.
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CITATION STYLE
Zukerman, I., Makalic, E., Niemann, M., & George, S. (2008). A probabilistic approach to the interpretation of spoken utterances. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5351 LNAI, pp. 581–592). https://doi.org/10.1007/978-3-540-89197-0_53
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