Paper: Learning To Generate Naturalistic Utterances Using Reviews In Spoken Dialogue Systems

ACL ID P06-1034
Title Learning To Generate Naturalistic Utterances Using Reviews In Spoken Dialogue Systems
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2006
Authors

Spoken language generation for dialogue systems requires a dictionary of mappings between semantic representations of con- cepts the system wants to express and re- alizations of those concepts. Dictionary creation is a costly process; it is currently done by hand for each dialogue domain. We propose a novel unsupervised method for learning such mappings from user re- views in the target domain, and test it on restaurant reviews. We test the hypothesis that user reviews that provide individual ratings for distinguished attributes of the domain entity make it possible to map re- view sentences to their semantic represen- tation with high precision. Experimental analyses show that the mappings learned cover most of the domain ontology, and provide good linguistic variation. A sub- jective us...