BibSonomy publications for /user/diego_ma/dialogue_systemFri Dec 14 02:43:14 CET 2007ACM Computing Surveys190-169Spoken Dialogue Technology: Enabling the Conversational User Interface342002speech dialogue_system Spoken dialogue systems allow users to interact with computer-based applications such as databases and expert systems by using natural spoken language. The origins of spoken dialogue systems can be traced back to Artificial Intelligence research in the 1950s concerned with developing conversational interfaces. However, it is only within the last decade or so, with major advances in speech technology, that large-scale working systems have been developed and, in some cases, introduced into commercial environments. As a result many major telecommunications and software companies have become aware of the potential for spoken dialogue technology to provide solutions in newly developing areas such as computer-telephony integration. Voice portals, which provide a speech-based interface between a telephone user and Web-based services, are the most recent application of spoken dialogue technology. This article describes the main components of the technology---speech recognition, language understanding, dialogue management, communication with an external source such as a database, language generation, speech synthesis---and shows how these component technologies can be integrated into a spoken dialogue system. The article describes in detail the methods that have been adopted in some well-known dialogue systems, explores different system architectures, considers issues of specification, design, and evaluation, reviews some currently available dialogue development toolkits, and outlines prospects for future development.Fri Dec 14 02:41:35 CET 2007Sanibel IslandProc. of the 11th International Florida Artificial Intelligence Research Symposium153-157Responding to Unexpected Student Utterances in {CIRCSIM}-Tutor v.3: Analysis of transcripts1998tutoring_system dialogue_system Fri Dec 14 02:41:34 CET 2007DaytonProc. of Midwest Artificial Intelligence and Cognitive Science Society Conference124-131Relationship between Tutorial Goals and Sentence Structure in a Corpus of Tutoring Transcripts1998tutoring_system dialogue_system Fri Dec 14 02:39:27 CET 2007IEEE Computer451-56Automated Natural Spoken Dialog352002speech dialogue_system The next generation of voice-based interface technology will enable easy-to-use automation of new and existing communication services, making human-machine interaction more natural.Fri Dec 14 02:39:26 CET 2007Proc. of the 1997 Florida Artificial Intelligence Research Symposium, FLAIRSSome Phenomena Handled by the {CIRCSIM}-Tutor Version 3 Input UnderstanderForthcomingtutoring_system dialogue_system Fri Dec 14 02:39:03 CET 2007Niagara-on-the-Lake, OntarioProc. of the Ninth International Workshop on Natural Language Generation (INLG-9)280-283System Demonstration Content Planning as the Basis for an Intelligent Tutoring System1998tutoring_system dialogue_system Fri Dec 14 02:39:02 CET 2007Online Procs. of the 1996 Midwest Artificial Intelligence and Cognitive Science ConferenceUsing a Text Planner to Model the Behavior of Human Tutors in an ITS1996tutoring_system dialogue_system Fri Dec 14 02:39:01 CET 2007Procs. of the AAAI 1997 Spring Symposium on Computational Models for Mixed-Initiative InteractionDegrees of Mixed-Initiative Interaction in an Intelligent Tutoring System1997tutoring_system dialogue_system Fri Dec 14 02:35:44 CET 2007Bellagio, ItalyProc. 3rd International Workshop on Human-Computer Conversationhttp://lithwww.epfl.ch/\~{}pallotta/publications.htmlThe role of robust semantic analysis in spoken language dialogue systems2000dialogue_system In this paper we summarized a framework for designing grammar-based procedure for the automatic extraction of the semantic content from spoken queries. Starting with a case study and following an approach which combines the notions of fuzziness and robustness in sentence parsing, we showed we built practical domain-dependent rules which can be applied whenever it is possible to superimpose a sentence-level semantic structure to a text without relying on a previous deep syntactical analysis. This kind of procedure can be also profitably used as a pre-processing tool in order to cut out part of the sentence which have been recognized to have no relevance in the understanding process. In the case of particular dialogue applications where there is no need to build a complex semantic structure (e.g. word spotting or excerpting) the presented methodology may represent an efficient alternative solution to a sequential composition of deep linguistic analysis modules. Even if the query generation problem may not seem a critical application it should be held in mind that the sentence processing must be done on-line. Having this kind of constraints we cannot design our system without caring for efficiency and thus provide an immediate response. Another critical issue is related to whole robustness of the system. In our case study we tried to make experiences on how it is possible to deal with an unreliable and noisy input without asking the user for any repetition or clarification. This may correspond to a similar problem one may have when processing text coming from informal writing such as e-mails, news and in many cases Web pages where it is often the case to have irrelevant surrounding information.