... 19-24, 2011.c2011 Association for Computational LinguisticsSemantic Information and Derivation Rules for Robust Dialogue ActDetection in a SpokenDialogue System Wei-Bin Liang1Chung-Hsien ... WtThe spoken language under-standing (SLU) module converts Wtto an abstractrepresentation of the user s dialogue act (DA). The dialogue management (DM) module determines the user s dialogue ... method of dialogue act de-tection for robust spokendialogue system, we adoptthe commonly-used Wizard-of-Oz approach (Fraserand Gilbert, 1991) to harvest the Tainan-city tour-guiding dialogue...
... Association for Computational Linguistics, pages 46–50,Avignon, France, April 23 - 27 2012.c2012 Association for Computational LinguisticsA Statistical SpokenDialogueSystem using Complex User ... statistical spokendialoguesystem thatuses automatic belief compression to rea-son over complex user goal sets. Reasoningover the power set of possible user goals al-lows complex sets of user goals ... as acentral challenge for the field of spoken dialogue systems, proposing the use of automatic compres-sion techniques to allow for extended accuraterepresentations of user goals. This paper...
... reliable and straighforward approximation of the utterance meaning than speech acts, and should not be ignored in the definition of context models for spokendialogue systems. 5 Conclusions ... point. For the pruned topic types, we reserved 10 ran- domly picked dialogues for testing (each test file con- tained about 400-500 test utterances), and used the other 70 dialogues for training ... management forspokendialogue systems. Finally, statistical modelling is prone to sparse data problems, and we need to consider ways to overcome inaccuracies in calculating mutual information....
... framework for evaluat-ing spokendialogue agents. In Proceedings of the ACL, 271–280 M. Walker and R. Passonneau. 2001. DATE: a dia-logue act tagging scheme forevaluation of spoken dialogue systems. ... prac-ticable dialogue systems (McTEAR, 2002), such as air travel information service system, weather forecast system, automatic banking system, auto-matic train timetable information system, and the ... method, a spoken dialogue systemfor medical domain with multiple services was investigated. Three main services: registration information service, clinic information service, and FAQ information...
... robust spokendialoguesystemfor a newtask currently requires considerable effort, includ-ing extensive data collection, grammar develop-ment, and building a dialogue manager that drivesthe system ... 85–88, Ann Arbor, June 2005.c2005 Association for Computational LinguisticsTwo diverse systems built usinggeneric components forspoken dialogue (Recent Progress on TRIPS)James Allen, George ... USAstent@cs.sunysb.eduAbstractThis paper describes recent progress on theTRIPS architecture for developing spoken- lan-guage dialogue systems. The interactive postersession will include demonstrations of two...
... experience with spoken dialogue systems. The structure of the interactionwith the system was the same for both groups.They were given minimal written instruction onhow to use the system before the ... the No Help con-152Targeted Help forSpokenDialogue Systems:intelligent feedback improves naive users' performanceBeth Ann HockeyResearch Institute for AdvancedComputer Science (RIACS),NASA ... use of user utterances thatare out-of-coverage of the main dialogue system recognizer to provide the user with immediatefeedback, tailored to what the user said, for casesin which the system...
... Moore, andClifford Nass. 2007. The influence of user tailoringand cognitive load on user performance in spoken dialogue systems. In Proc. of the 10th InternationalConference of Spoken Language ... trainstrategies forDialogue Management, see for ex-ample (Young et al., 2007). A user simulation for NLG is very similar, in that it is a predictive modelof the most likely next user act. However, this user act ... 2002. User- tailored generation for spoken dialogue: an experiment. In In Proc. of IC-SLP.Amanda Stent, Rashmi Prasad, and Marilyn Walker.2004. Trainable sentence planning for complex in-formation...
... wizard-of-oz interface to study information pre-sentation strategies forspokendialogue systems. InProc. of the 1st International Workshop on Spoken Dialogue Systems.Crystal Nakatsu. 2008. ... LanguageResources and Evaluation (LREC).Andi Winterboer, Jiang Hu, Johanna D. Moore, andClifford Nass. 2007. The influence of user tailoringand cognitive load on user performance in spoken dialogue systems. ... or ellipsis), contrasts1011W. Eckert, E. Levin, and R. Pieraccini. 1997. User modelingforspokendialoguesystem evaluation. InProc. of the IEEE workshop on Automatic SpeechRecognition and...
... some implications for resumption strategies in an in-vehicle dialogue system. 1 IntroductionMaking it useful and enjoyable to use a dialogue system is always important. The dialogue shouldbe ... That means that the most common rea-son for the speaker to interrupt is to ask for or giveinformation that is crucial for the driving task (asopposed for the other and traffic domains, whichare ... bythe driving task), the user might need informationthat is crucial for the driving task (e.g. get nav-igation instructions), or to pause the dialogue inorder to enable the user to concentrate...
... the model of user actions,not the model of user goal evolution.2 MethodBefore we can estimate a user model, we must definea larger model of human-computer dialogs, of whichthe user model is ... At.Recall that the user model is a multinomial distri-bution Pr(At| St, Ut; θ) parameterized by a vectorθ. Based on the number user actions, system actions,and user states, θ is a vector ... sequenceof system actions and observed user actions: x =(S0,˜A0, S1,˜A1, . . .). Here Stdenotes the system action, and˜Atthe output of the ASR engine whenapplied to the true user...
... Group on Discourse and Dialogue Workshop on Discourse and Dialogue (SIGdial). D. J. Litman and S. Silliman, 2004. ITSPOKE: An Intelligent Tutoring SpokenDialogue System. Companion Proceedings ... Wrappers for Feature Subset Selection. Artificial Intelligence, Volume 97, Issue 1-2. D. J. Litman and K. Forbes-Riley, 2004. Annotating Student Emotional States in Spoken Tutoring Dialogues. ... Accuracy using best features for Precision of Emotional/Non-Emotional 5 Conclusion We have shown Co-training to be a promising approach for predicting emotions with spoken dialogue data. We have...
... under- standing system developed forspoken language applications. This paper describes the details of the system, and includes relevant measurements of size, efficiency, and performance of each ... allows us to enforce a very coarse form of parse preferences (for exam- ple, prefering complete sentences to sentence frag- ments). These coarse preferences could also be enforced by the parse ... understanding system, there is a tension between robustness and correct- ness. Forgiving an error risks throwing away cru- cial information; furthermore, devices added to a system to enhance...