Lexical Structure for Dialogue Act Recognition

Abstract

This paper deals with automatic dialogue acts (DAs) recognition in Czech. Dialogue acts are sentence-level labels that represent different states of a dialogue, such as questions, hesitations, ... In our application, a multimodal reservation system, four dialogue acts are considered: statements, orders, yes/no questions and other questions. The main contribution of this work is to propose and compare several approaches that recognize dialogue acts based on three types of information: lexical information, prosody and word positions. These approaches are tested on a Czech Railways corpus that contains human-human dialogues, which are transcribed both manually and with an automatic speech recognizer for comparison. The experimental results confirm that every type of feature (lexical, prosodic and word positions) bring relevant and somewhat complementary information. The proposed methods that take into account word positions are especially interesting, as they bring global information about the structure of the sentence, at the opposite of traditional n-gram models that only capture local cues. When word sequences are estimated from a speech recognizer, the resulting decrease of accuracy of all proposed approaches is very small (about 3 %), which confirms the capability of the proposed approaches to perform well in real applications.