... When interacting with ITSPOKE, users first type an essay answering a qualitative physics problem using a graphical user interface. ITSPOKE then engages the userinspokendialogue (using head-mounted ... Software Interface Agents. User Modeling and User- Adapted Interaction, 8(3-4). M. Rotaru and D. Litman. 2006. Exploiting Discourse Structure for SpokenDialogue Performance Analy-sis. In Proc. ... Q14-16 were included to probe user s post tutoring perceptions. We find a trend that in the NM problems it was easier for users to under-stand the system’s main point (Q14). However, in terms...
... of interest for any rational user. All dominantoptions represent some tradeoff, but depending onthe user s interest, some of them are more interest-ing tradeoffs than others.Pruning dominated ... that inte-grates user modelling with automated clustering.65 user model is available, it enables the system todetermine which options and which attributes ofoptions are likely to be of interest ... forcooperative response generation in information dialogues. In AAAI/IAAI 1999 pp. 148–155.M. Steedman 2000. Information structure and the syntax-phonology interface. In Linguistic Inquiry, 31(4): 649–689.A....
... evaluat-ing spokendialogue agents. In Proceedings of the ACL, 271–280 M. Walker and R. Passonneau. 2001. DATE: a dia-logue act tagging scheme for evaluation of spoken dialogue systems. In ... 941Proceedings of the COLING/ACL 2006 Main Conference Poster Sessions, pages 937–944,Sydney, July 2006.c2006 Association for Computational LinguisticsStochastic Discourse Modeling inSpokenDialogue ... core technology of the spoken dia-logue systems, since the more accurate information obtained by the machine (Higashinaka et al., 2004), the more possibility to finish the dialogue task. Practical...
... tuning.Future work points in two directions: first, inte-grating our methodology into working ISU-based dialogue systems and determining whether or notthey improve in terms of standard dialogue ... used by a dialogue manager to decide appro-priate system reactions. The approach is novel in combining machine learning with n-best processingfor spokendialoguesystems using the InformationState ... understand-ing. In Proceedings of ACL-93.Malte Gabsdil. 2003. Classifying Recognition Re-sults for SpokenDialogue Systems. In Proceed-ings of the Student Research Workshop at ACL-03.Perry R. Hinton....
... consistent user simulations for dialog systems. In Proceedingsof Interspeech 2007, Antwerp, Belgium.T. Akiba and H. Tanaka. 1994. A Bayesian approachfor User Modelling inDialogue Systems. In Pro-ceedings ... therefore that a spoken dialogue system (SDS) must be capable of observing the user s dialogue behaviour, modelling his/her do-main knowledge, and adapting accordingly, justlike human interlocutors. ... LanguageGeneration as Planning Under Uncertainty for Spo-ken Dialogue Systems. In Proc. EACL’09.V. Rieser and O. Lemon. 2010. Optimising informa-tion presentation for spokendialogue systems. In Proc. ACL....
... developed for bilingual dialoguein a voice-to-voice machine translation application. In this application, the Dialogue Manager is available for meta- dialogues with either user (as in Could you ... as a function of interaction style; its simple protocol specifies conditions for interrupting user speech for permitting interruption by the user, when to initiate repair dialogues, and how ... Actors. In "Automated SpokenDialogue Systems& quot;, S. Lu- perFoy, ed. MIT Press (forthcoming). LuperFoy. S (1992) The Representation of Multi- modal User- Interface Dialogues Using Discourse...
... s ta lkabout NOW: Identifying cue phrases intonationally. In Proc. 25th ACL, pages 163–171.Minqing Hu and Bing Liu. 2005. Mining and summarizingcustomer reviews. In Proc. KDD, pages 168–177.Alistair ... on which Minipar was trained, the outputof Minipar can be inaccurate, leading to failure in conversion. We check whether conversion is suc-cessful in the filtering stage.2.4 FilteringThe goal ... mappingsfor multi-relation mappings, with those contain-ing a food or service relation occurring more fre-quently as in the single scalar-valued relation map-pings. We found only 21 combinations...
... 1997. Utterance units inspoken dialogue. In Elisabeth Maier, Marion Mast, and Susann LuperFoy, editors, Dialogue Pro- cessing inSpoken Language Systems, pages 125-140. Springer-Verlag. Marilyn ... Implementation Using ISSS, we have developed several experimen- tal Japanese spokendialogue systems, including a meeting room reservation system. The architecture of the systems is shown in Fig- ure ... solved by incremen- tal understanding, which means obtaining the most plausible interpretation of user utterances every time a word hypothesis is inputted from the speech recog- nizer. For incremental...
... below 400ms, and increasing the thresh-old value in increments of 100ms.Table 2 shows the values for the highest perform-ing models. The model that only inserts continuers in pauses over 900 ... point out that users of speechinterface systems need feedback, too, especially sincethe system's silence could mean either of two very dif-ferent things: that it is waiting for user input, ... describework on building spokendialoguesystems for convers-ing with mobile robots, and this is a setting where com-plex instructions naturally arise. For example, in onescenario,1 users attempt...
... ignored in the definition of context models for spokendialogue systems. 5 Conclusions The paper has presented a probabilistic topic model to be used as a context model for spokendialogue systems. ... maintain robustness of spokendialoguesystems can be defined in terms of topic types rather than speech acts. Our model uses actually occurring words and topic information of the domain, ... context. InDialogue Processing inSpoken Dialogue Systems, pages 60-64. Proceedings of the ECAI'96 Workshop, Budapest, Hungary. N. Reithinger and E. Maier. 1995. Utilizing statisti- cal dialogue...
... of entrainment capturedifferent aspects of dialogue coordination and thatexploring various formulations of entrainment de-serves future attention.3.3 Dialogue coordinationThe coordination ... correlates with task success andminimal interruptions—important goals of SDS. In future work we will explore the consequences ofsystem entrainment to SDS users in helping systems achieve these goals, ... BrainSciences, 27:169–226.D. Reitter and J. Moore. 2007. Predicting success in dialogue. ACL’07.D. Reitter, F. Keller, and J.D. Moore. 2006. Compu-tational Modelling of Structural Priming in...
... Generating canonical examples using candi-date words. In (under submission).G. Correll, I. Lewin, and M. Rayner. 2002. Addingintelligent help to mixed-initiative spoken dialogue systems. In Proceedings ... otherwise the user islikely to be misled into thinking that a particulartype of dialogue- move is impossible in the system.Looking for in- coverage words is fairly robust.Even when the user produces ... all of the trials we included, the goal entitywas explicitly mentioned in the dialogue. Accord-ing to this criterion only 44% of users in the Helpcondition and 18% of users in the No Help con-152Targeted...
... corpora contain data from“overhearer” experiments targeted to InformationPresentation in dialogues in the restaurant domain.While we are ultimately interested in how hearersengaged in dialogues ... user tailoringand cognitive load on user performance in spoken dialogue systems. In Proc. of the 10th InternationalConference of Spoken Language Processing (Inter-speech/ICSLP).SJ Young, J Schatzmann, ... evaluated a new model for Nat-ural Language Generation (NLG) inSpoken Dia-logue Systems, based on statistical planning. Aftermotivating and presenting the model, we studiedits use in Information...
... 2007. The in uence of user tailoringand cognitive load on user performance in spoken dialogue systems. In Proc. of the 10th InternationalConference of Spoken Language Processing (Inter-speech/ICSLP).SJ ... wizard-of-oz interface to study information pre-sentation strategies for spokendialogue systems. In Proc. of the 1st International Workshop on Spoken Dialogue Systems. Crystal Nakatsu. 2008. Learning ... real users: the TALK TownInfo Evaluation. In IEEE/ACL Spoken Language Technology.Oliver Lemon. 2008. Adaptive Natural LanguageGeneration inDialogue using Reinforcement Learn-ing. In Proceedings...
... biddingapproach to turn-taking. In 1st International Work-shop on SpokenDialogue Systems. G. Skantze and D. Schlangen. 2009. Incremental di-alogue processing in a micro-domain. In Proceed-ings ... filler results in the utterance of ”inform drinkd1.” A sample dialogue fragment using the Single-Utterance approach is shown in Table 2. Noticethat in Line 3 the system informs the user thattheir ... Build-ing 10,000 spoken- dialogue systems. In ICSLP,Philadelphia, Oct.M. Walker and S. Whittaker. 1990. Mixed initiative in dialoge: an investigation into discourse segmen-tation. In Proceedings...