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Some background on dialogue management and conversational speech for dialogue systems

Research output: Contribution to journalReview ArticleScientificpeer-review

Details

Original languageEnglish
Pages (from-to)128-139
Number of pages12
JournalComputer Speech and Language
Volume25
Issue number2
DOIs
Publication statusPublished - Apr 2011
Publication typeA2 Review article in a scientific journal

Abstract

Several dialogue management (DM) architectures and conversational speech for dialogue systems are presented. Basic types of DM systems include dialogue grammars and frames, plan-based and collaborative systems, and conversational games theory. DM architectures include SmartKom, Trindi, WITAS, CONVERSE, COMIC, agent-based dialogue management, and DM and automatic speech recognition (ASR) language modeling. All data collection tasks should be tailored for the conversational scenario under consideration as each scenario can present different properties. It is shown in the multimodal dialogue system that turn taking can usually be achieved by a fusion of gesture, gaze, and intonation. Intonation within the speech signal informs the dialogue manager when new information is introduced into the current conversation. By placing established emotion detection methods within the recursive nature of conversation we can consider discourse as the exploitation of the shared set of interaction affordances.

Keywords

  • Dialogue architectures, Dialogue management, Dialogue systems, Emotion detection, Human-computer interaction