Skip to main content Accessibility help
×
Hostname: page-component-76fb5796d-wq484 Total loading time: 0 Render date: 2024-04-28T06:04:28.812Z Has data issue: false hasContentIssue false

4 - Dialogue and compound contributions

from Part I - Joint construction

Published online by Cambridge University Press:  05 July 2014

Matthew Purver
Affiliation:
University of London
Julian Hough
Affiliation:
University of London
Eleni Gregoromichelaki
Affiliation:
King's College London
Amanda Stent
Affiliation:
AT&T Research, Florham Park, New Jersey
Srinivas Bangalore
Affiliation:
AT&T Research, Florham Park, New Jersey
Get access

Summary

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2014

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aist, G., Allen, J. F., Campana, E., Gomez Gallo, C., Stoness, S., Swift, M., and Tanenhaus, M. K. (2007). Incremental dialogue system faster than, preferred to its nonincremental counterpart. In Proceedings of the Annual Conference of the Cognitive Science Society (CogSci), pages 761-766, Nashville, TN. Cognitive Science Society.Google Scholar
Allen, J. F., Byron, D., Dzikovska, M., Ferguson, G., Galescu, L., and Stent, A. (2001). Towards conversational human-computer interaction. AIMagazine, 22(4):27-37.Google Scholar
Asher, N. and Lascarides, A. (2008). Commitments, beliefs and intentions in dialogue. In Proceedings of the Workshop on the Semantics and Pragmatics of Dialogue (LONDIAL), pages 9-36, London, UK. SemDial.Google Scholar
Betarte, G. and Tasistro, A. (1998). Extension of Martin-Lof type theory with record types and subtyping. In 25 Years of Constructive Type Theory, pages 21-10. Oxford University Press, Oxford, UK.Google Scholar
Brennan, S. E. and Schober, M. (2001). How listeners compensate for disfluencies in spontaneous speech. Journal of Memory and Language, 44(2):274-296.CrossRefGoogle Scholar
Burnard, L. (2000). Reference Guide for the British National Corpus (World Edition). Available from: http://www.natcorp.ox.ac.uk/archive/worldURG/urg.pdf. Accessed on 11/24/2013.Google Scholar
BuB, O., Baumann, T., and Schlangen, D. (2010). Collaborating on utterances with a spoken dialogue system using an ISU-based approach to incremental dialogue management. In Proceedings of the SIGdial Conference on Discourse and Dialogue (SIGDIAL), pages 233-236, Tokyo, Japan. Association for Computational Linguistics.Google Scholar
Cann, R., Kaplan, T., and Kempson, R. (2005). Data at the grammar-pragmatics interface: The case of resumptive pronouns in English. Lingua, 115(11): 1551-1577.CrossRefGoogle Scholar
Cooper, R. (2005). Records and record types in semantic theory. Journal of Logic and Computation, 15(2):99-112.CrossRefGoogle Scholar
De Smedt, K. (1990). IPF: An incremental parallel formulator. In Current Research in Natural Language Generation, pages 167-192. Academic Press, San Diego, CA.Google Scholar
De Smedt, K. (1991). Revisions during generation using non-destructive unification. In Proceedings of the European Workshop on Natural Language Generation (EWNLG), pages 63-70, Judenstein/Innsbruck, Austria. Association for Computational Linguistics.Google Scholar
De Smedt, K., Horacek, H., and Zock, M. (1996). Some problems with current architectures in natural language generation. In Adorni, G. and Zock, M., editors, Trends in Natural Language Generation: An Artificial Intelligence Perspective, pages 17-46. Springer LNCS, Berlin, Germany.Google Scholar
DeVault, D., Sagae, K., and Traum, D. (2009). Can I finish?: Learning when to respond to incremental interpretation results in interactive dialogue. In Proceedings of the SIGdial Conference on Discourse and Dialogue (SIGDIAL), pages 11-20, London, UK. Association for Computational Linguistics.Google Scholar
DeVault, D., Sagae, K., and Traum, D. (2011). Incremental interpretation and prediction of utterance meaning for interactive dialogue. Dialogue and Discourse, 2(1):143-170.CrossRefGoogle Scholar
Eshghi, A., Purver, M., and Hough, J. (2011). DyLan: Parser for dynamic syntax. Technical Report EECSRR-11-05, School of Electronic Engineering and Computer Science, Queen Mary University of London.Google Scholar
Ferreira, V. S. (1996). Is it better to give than to donate? Syntactic flexibility in language production. Journal of Memory and Language, 35(5):724-755.CrossRefGoogle Scholar
Gargett, A., Gregoromichelaki, E., Kempson, R., Purver, M., and Sato, Y. (2009). Grammar resources for modelling dialogue dynamically. Cognitive Neurodynamics, 3(4):347-363.CrossRefGoogle ScholarPubMed
Ginzburg, J. (2012). The Interactive Stance: Meaning for Conversations. Oxford University Press, Oxford, UK.CrossRefGoogle Scholar
Goodwin, C. (1979). The interactive construction of a sentence in natural conversation. In Psathas, G., editor, Everyday Language: Studies in Ethnomethodology, pages 97-121. Irvington, New York, NY.Google Scholar
Goodwin, C. (1981). Conversational Organization: Interaction between Speakers and Hearers. Academic Press, New York, NY.Google Scholar
Gregoromichelaki, E., Kempson, R., Purver, M., Mills, G. J., Cann, R., Meyer-Viol, W., and Healey, P. G. (2011). Incrementality and intention-recognition in utterance processing. Dialogue and Discourse, 2(1):199-233.CrossRefGoogle Scholar
Guhe, M. (2007). Incremental Conceptualization for Language Production. Lawrence Erlbaum Associates, Mahwah, NJ.Google Scholar
Guhe, M., Habel, C., and Tappe, H. (2000). Incremental event conceptualization and natural language generation in monitoring environments. In Proceedings of the International Conference on Natural Language Generation (INLG), pages 85-92, Mitzpe Ramon, Israel. Association for Computational Linguistics.Google Scholar
Healey, P. G. (2008). Interactive misalignment: The role of repair in the development of group sub-languages. In Cooper, R. and Kempson, R., editors, Language in Flux: Dialogue Coordination, Language Variation, Change and Evolution. College Publications, London, UK.Google Scholar
Healey, P. G., Purver, M., and Howes, C. (2010). Structural divergence in dialogue. In Abstracts of the Meeting of the Society for Text & Discourse, Chicago, IL. Society for Text & Discourse.Google Scholar
Hough, J. (2011). Incremental semantics driven natural language generation with self-repairing capability. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP), pages 79-84, Hissar, Bulgaria. Association for Computational Linguistics.Google Scholar
Howes, C, Purver, M., Healey, P. G., Mills, G. J., and Gregoromichelaki, E. (2011). On incre-mentality in dialogue: Evidence from compound contributions. Dialogue and Discourse, 2(1):279-311.CrossRefGoogle Scholar
Joshi, A. (1985). Tree adjoining grammars: How much context-sensitivity is required to provide reasonable structural descriptions? In Dowty, D., Karttunen, L., and Zwicky, A. M., editors, Natural Language Parsing: Psychological, Computational, and Theoretical Perspectives, pages 206-250. Cambridge University Press, Cambridge, UK.Google Scholar
Kamp, H. and Reyle, U. (1993). From Discourse to Logic: Introduction to Modeltheoretic Semantics of Natural Language, Formal Logic and Discourse Representation Theory. Kluwer Academic Publishers, Dordrecht, The Netherlands.Google Scholar
Kay, M. (1985). Parsing in functional unification grammar. In Dowty, D., Karttunen, L., and Zwicky, A. M., editors, Natural Language Parsing: Psychological, Computational and Theoretical Perspectives, pages 251-278. Cambridge University Press, Cambridge, UK.Google Scholar
Kempen, G. and Hoenkamp, E. (1987). An incremental procedural grammar for sentence formulation. Cognitive Science, 11(2):201-258.CrossRefGoogle Scholar
Kempson, R., Cann, R., Eshghi, A., Gregoromichelaki, E., and Purver, M. (2011). Ellipsis. In Lappin, S. and Fox, C., editors, The Handbook of Contemporary Semantic Theory. Wiley, New York, NY, 2nd edition.Google Scholar
Kempson, R., Meyer-Viol, W., and Gabbay, D. (2001). Dynamic Syntax: The Flow of Language Understanding. Blackwell, Oxford, UK.Google Scholar
Larsson, S. (2002). Issue-based Dialogue Management. PhD thesis, Department of Linguistics, Göteborg University.Google Scholar
Lascarides, A. and Asher, N. (2009). Agreement, disputes and commitments in dialogue. Journal of Semantics, 26(2):109-158.CrossRefGoogle Scholar
Lehnert, W. G. (1978). The Process of Question Answering: A Computer Simulation of Cognition. Lawrence Erlbaum Associates, Mahwah, NJ.Google Scholar
Lerner, G. H. (1991). On the syntax of sentences-in-progress. Language in Society, 20(3): 441-458.CrossRefGoogle Scholar
Lerner, G. H. (1996). On the “semi-permeable” character of grammatical units in conversation: Conditional entry into the turn space of another speaker. In Ochs, E., Schegloff, E. A., and Thompson, S. A., editors, Interaction and Grammar, pages 238-276. Cambridge University Press, Cambridge, UK.Google Scholar
Lerner, G. H. (2004). Collaborative turn sequences. In Lerner, G. H., editor, Conversation Analysis: Studies from the First Generation, pages 225-256. John Benjamins, Amsterdam, The Netherlands.CrossRefGoogle Scholar
Levelt, W. J. M. (1983). Monitoring and self-repair in speech. Cognition, 14(1):41-104.CrossRefGoogle Scholar
Levelt, W. J. M. (1989). Speaking: From Intention to Articulation. MIT Press, Cambridge, MA.Google Scholar
Milward, D. (1991). Axiomatic Grammar, Non-Constituent Coordination, Incremental Interpretation. PhD thesis, University of Cambridge.Google Scholar
Neumann, G. (1994). A Uniform Computational Model for Natural Language Parsing and Generation. PhD thesis, Universitaat des Saarlandes, Saarbrücken.Google Scholar
Neumann, G. (1998). Interleaving natural language parsing and generation through uniform processing. Artificial Intelligence, 99(1):121-163.CrossRefGoogle Scholar
Neumann, G. and van Noord, G. (1994). Reversibility and self-monitoring in natural language generation. In Strzalkowski, T., editor, Reversible Grammar in Natural Language Processing, pages 59-96. Kluwer, Dordrecht, The Netherlands.Google Scholar
Ono, T. and Thompson, S. A. (1993). What can conversation tell us about syntax? In Davis, P., editor, Alternative Linguistics: Descriptive and Theoretical Modes, pages 213-271. John Benjamins, Amsterdam, The Netherlands.Google Scholar
Otsuka, M. and Purver, M. (2003). Incremental generation by incremental parsing: Tactical generation in dynamic syntax. In Proceedings of the CLUK Colloquium, pages 93-100, Edinburgh, Scotland. The UK Special Interest Group for Computational Linguistics.Google Scholar
Pickering, M. and Garrod, S. (2004). Toward a mechanistic psychology of dialogue. Behavioral and Brain Sciences, 27(2):169-226.CrossRefGoogle Scholar
Poesio, M. and Rieser, H. (2010). Completions, coordination, and alignment in dialogue. Dialogue and Discourse, 1:1-89.CrossRefGoogle Scholar
Poesio, M. and Traum, D. R. (1997). Conversational actions and discourse situations. Computational Intelligence, 13(3):309-347.CrossRefGoogle Scholar
Purver, M., Cann, R., and Kempson, R. (2006). Grammars as parsers: Meeting the dialogue challenge. Research on Language and Computation, 4(2-3):289-326.CrossRefGoogle Scholar
Purver, M., Eshghi, A., and Hough, J. (2011). Incremental semantic construction in a dialogue system. In Proceedings of the International Conference on Computational Semantics, pages 365-369, Oxford, UK. Association for Computational Linguistics.Google Scholar
Purver, M., Gregoromichelaki, E., Meyer-Viol, W., and Cann, R. (2010). Splitting the I's and crossing the you's: Context, speech acts and grammar. In Proceedings of the Workshop on the Semantics and Pragmatics of Dialogue (PozDial), pages 43-50, Poznán, Poland. SemDial.Google Scholar
Purver, M., Howes, C., Healey, P. G., and Gregoromichelaki, E. (2009). Split utterances in dialogue: A corpus study. In Proceedings of the SIGdial Conference on Discourse and Dialogue (SIGDIAL), pages 262-271, London, UK. Association for Computational Linguistics.Google Scholar
Purver, M. and Kempson, R. (2004a). Context-based incremental generation for dialogue. In Proceedings of the International Conference on Natural Language Generation (INLG), pages 151-160, Brockenhurst, UK. Springer.Google Scholar
Purver, M. and Kempson, R. (2004b). Incrementality, alignment and shared utterances. In Proceedings of the Workshop on the Semantics and Pragmatics of Dialogue (Catalog), pages 85-92, Barcelona, Spain. SemDial.Google Scholar
Purver, M. and Otsuka, M. (2003). Incremental generation by incremental parsing: Tactical generation in dynamic syntax. In Proceedings of the European Workshop on Natural Language Generation (ENLG), pages 79-86, Budapest, Hungary. Association for Computational Linguistics.Google Scholar
Reiter, E. and Dale, R. (2000). Building Natural Language Generation Systems. Cambridge University Press, Cambridge, UK.CrossRefGoogle Scholar
Rühlemann, C. and McCarthy, M. (2007). Conversation in Context: A Corpus-Driven Approach. Continuum, London, UK.Google Scholar
Sato, Y. (2011). Local ambiguity, search strategies and parsing in dynamic syntax. In Gregoromichelaki, E., Kempson, R., and Howes, C., editors, The Dynamics ofLexical Interfaces. CSLI Publications, Stanford, CA.Google Scholar
Saxton, M. (1997). The contrast theory of negative input. Journal of Child Language, 24(1): 139-161.CrossRefGoogle ScholarPubMed
Schegloff, E. (1979). The relevance of repair to syntax-for-conversation. In Givon, T., editor, Discourse and Syntax, pages 261-286. Academic Press, New York, NY.Google Scholar
Schegloff, E. (2007). Sequence Organization in Interaction: A Primer in Conversation Analysis I. Cambridge University Press, Cambridge, UK.CrossRefGoogle Scholar
Schlangen, D. and Skantze, G. (2009). A general, abstract model of incremental dialogue processing. In Proceedings of the Conference of the European Chapter of the Associationfor Computational Linguistics (EACL), pages 710-718, Athens, Greece. Association for Computational Linguistics.Google Scholar
Schlangen, D. and Skantze, G. (2011). A general, abstract model of incremental dialogue processing. Dialogue and Discourse, 2(1):83-111.CrossRefGoogle Scholar
Shieber, S. M. (1988). A uniform architecture for parsing and generation. In Proceedings of the International Conference on Computational Linguistics (COLING), pages 614-619, Budapest, Czech Republic. International Committee on Computational Linguistics.Google Scholar
Skantze, G. and Hjalmarsson, A. (2010). Towards incremental speech generation in dialogue systems. In Proceedings of the SIGdial Conference on Discourse and Dialogue (SIGDIAL), pages 1-8, Tokyo, Japan. Association for Computational Linguistics.Google Scholar
Skantze, G. and Schlangen, D. (2009). Incremental dialogue processing in a micro-domain. In Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics (EACL), pages 745-753, Athens, Greece. Association for Computational Linguistics.Google Scholar
Skuplik, K. (1999). Satzkooperationen. definition und empirische untersuchung. Technical Report 1999/03, Bielefeld University.Google Scholar
Sturt, P. and Crocker, M. (1996). Monotonic syntactic processing: A cross-linguistic study of attachment and reanalysis. Language and Cognitive Processes, 11(5):449-494.CrossRefGoogle Scholar
Szczepek Reed, B. (2000). Formal aspects of collaborative productions in English conversation. Interaction and Linguistic Structures, 17.Google Scholar
Thompson, H. (1977). Strategy and tactics: A model for language production. In Papers from the Regional Meeting of the Chicago Linguistic Society, volume 13, pages 651-668, Chicago, IL. Chicago Linguistic Society.Google Scholar
van Wijk, C. and Kempen, G. (1987). A dual system for producing self-repairs in spontaneous speech: Evidence from experimentally elicited corrections. Cognitive Psychology, 19(4): 403-440.CrossRefGoogle Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×