Two-Layer Semantic Entity Detection and Utterance Validation for Spoken Dialogue Systems

Abstract

In this paper we present a novel method for semantic entity detection in a limited domain for spoken language understanding. The target domain of this method is a dialogue system for an interactive training of air traffic controllers (ATC). The method comprises of two layers of detection. First layer uses formerly proposed method for semantic entity detection to extract domain-dependent set of semantic entities. This semantic entities are modelled using context-free grammars. To detect mispronounced words or words which do not comply with the ATC radio-telephony rules we use the second layer of semantic entity detection. Together with that, we assign a semantic meaning to the utterance. We also discuss the possibility of using this approach for semantic-based correction of an utterance. The experiments were performed on transcribed data as well as on an output from speech recognizer.