Some background on dialogue management and conversational speech for dialogue systems
Research output: Contribution to journal › Review Article › Scientific › peer-review
|Number of pages||12|
|Journal||Computer Speech and Language|
|Publication status||Published - Apr 2011|
|Publication type||A2 Review article in a scientific journal|
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.