A Probabilistic Approach to the Interpretation of Spoken Utterances

Authors:
Ingrid Zukerman;Enes Makalic;Michael Niemann;Sarah George
Affiliations:
Faculty of Information Technology, Monash University, Clayton, Australia 3800;Faculty of Information Technology, Monash University, Clayton, Australia 3800;Faculty of Information Technology, Monash University, Clayton, Australia 3800;Faculty of Information Technology, Monash University, Clayton, Australia 3800
Venue:
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Year:
2008

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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.