Hostname: page-component-78c5997874-mlc7c Total loading time: 0 Render date: 2024-11-04T21:07:30.426Z Has data issue: false hasContentIssue false
  • English
  • Français

Natural discourse reference generation reduces cognitive load in spoken systems

Published online by Cambridge University Press:  10 September 2010

E. CAMPANA ,
M. K. TANENHAUS ,
J. F. ALLEN  and
R. REMINGTON
E. CAMPANA
Affiliation:
Psychology Department, 699 S. Mill Avenue, Arizona State University, Tempe, AZ 85281, USA email: [email protected]
M. K. TANENHAUS
Affiliation:
Brain and Cognitive Sciences, RC Box 270268, University of Rochester, Rochester, NY 14627, USA email: [email protected]
J. F. ALLEN
Affiliation:
Computer Science, RC Box 270226, University of Rochester, Rochester, NY 14627, USA email: [email protected]
R. REMINGTON
Affiliation:
School of Psychology, McElwain Building, The University of Queensland, St. Lucia QLD 4072, Australia email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

The generation of referring expressions is a central topic in computational linguistics. Natural referring expressions – both definite references like ‘the baseball cap’ and pronouns like ‘it’ – are dependent on discourse context. We examine the practical implications of context-dependent referring expression generation for the design of spoken systems. Currently, not all spoken systems have the goal of generating natural referring expressions. Many researchers believe that the context-dependency of natural referring expressions actually makes systems less usable. Using the dual-task paradigm, we demonstrate that generating natural referring expressions that are dependent on discourse context reduces cognitive load. Somewhat surprisingly, we also demonstrate that practice does not improve cognitive load in systems that generate consistent (context-independent) referring expressions. We discuss practical implications for spoken systems as well as other areas of referring expression generation.

Type
Articles
Information
Natural Language Engineering , Volume 17 , Issue 3 , July 2011 , pp. 311 - 329
Copyright
Copyright © Cambridge University Press 2010

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

Appelt, D. E. 1985. Planning English referring expressions. Artificial Intelligence 26 (1): 1–33.CrossRefGoogle Scholar
Belz, A., and Varges, S. 2007. Generation of repeated references to discourse entities. In Proceedings of the 11th European Workshop on Natural Language Generation (ENLG'07), pp. 9–16.Google Scholar
Belz, A., Gatt, A., Reiter, E., and Viethen, J. 2007. Referring expression generation (Chapter 3). In White, M. and Dale, R. (eds.), Report of the Workshop on Shared Tasks and Comparative Evaluation in Natural Language Generation, pp. 17–30.Google Scholar
Brown-Schmidt, S., Campana, E., and Tanenhaus, M. K. 2005. Real-time reference resolution by nave participants during a task-based unscripted conversation. In Trueswell, J. and Tanenhaus, M. K. (eds.), Approaches to Studying World-Situated Language Use: Bridging the Language-as-Product and Language-as-Action Traditions, pp. 1–22. Boston, MA: MIT Press.Google Scholar
Brown-Schmidt, B. S., and Tanenhaus, M. K. 2008. Real-time investigation of referential domains in unscripted conversation: a targeted language game approach. Cognitive Science 32: 643–684.CrossRefGoogle ScholarPubMed
Campana, E., Brown-Schmidt, S., and Tanenhaus, M. K. 2002. Reference resolution by human partners in a natural interactive problem-solving task. In Proceedings of the 7th International Conference on Spoken Language Processing (ICSLP), pp. 2057–2060, Denver, CO, USA.Google Scholar
Churcher, G., Atwell, E., and Souter, C. 1996. Dialogues in air traffic control. In Luperfoy, S., Nijholt, A. and Veldhuijzen van Zanten, G. (eds.), Dialogue Management in Natural Language Systems, Proceedings of the 11th Twente Workshop on Language Technology.Google Scholar
Clark, H. H. 1992. Arenas of Language Use. Chicago, IL: University of Chicago Press.Google Scholar
Clark, P., Harrison, P., Murray, W. R., and Thompson, J. 2009. Naturalness vs. predictability: a key debate in controlled languages. Presented at the Workshop on Controlled Natural Language (CNL 2009), Marettimo Island, Italy.Google Scholar
Clark, H. H., and Wilkes-Gibbs, D. 1986. Referring as a collaborative process. Cognition 22: 1–39.CrossRefGoogle ScholarPubMed
Cowan, N. 2005. Working Memory Capacity. Hove, East Sussex, UK: Psychology Press.Google Scholar
Croitoru, M., and van Deemter, Kees 2007. A conceptual graph approach to the generation of referring expressions. In Proceedings of the 2007 International Joint Conference on Artificial Intelligence (IJCAI), pp. 2456–2461, Hyderabad, India.Google Scholar
Dale, R. 1988. Generating Referring Expressions in a Domain of Objects and Processes. PhD dissertation, Edinburgh, UK: University of Edinburgh.Google Scholar
Dale, R., and Reiter, E. 1995. Computational interpretations of the Gricean Maxims in the generation of referring expressions. Cognitive Science 19: 233–263.CrossRefGoogle Scholar
DeVault, D., Rich, C., and Sidner, C. L. 2004. Natural language generation and discourse context: computing distractor sets from the focus stack. In Proceedings of the International Florida Artificial Intelligence Research Symposium (FLAIRS).Google Scholar
Dickson, P. 2008. Baseball's Greatest Quotations: An Illustrated Treasury of Baseball Quotations and Historical Lore (Revised Edition). New York: HarperCollins.Google Scholar
Hanowski, R. J., Olson, R. L., Hickman, J. S., and Dingus, T. A. 2006. The 100-car naturalistic driving study: a descriptive analysis of light vehicle-heavy vehicle interactions from the light vehicle drivers perspective. Technical Report FMCSA-RRR-06-004, National Technical Information Service, US Department of Transportation.CrossRefGoogle Scholar
Gatt, A., and van Deemter, K. 2007. Lexical choice and conceptual perspective in the generation of plural referring expressions. Journal of Logic, Language and Information (JoLLI), 16 (4): 423–443.CrossRefGoogle Scholar
Gatt, A., and van Deemter, K. 2009. Generating plural NPs in discourse: evidence from the GNOME corpus. In Proceedings of the CogSci 2009 Workshop on the Production of Referring Expressions: Bridging the Gap between Computational and Empirical Approaches to Reference (PRE-CogSci 2009).Google Scholar
Greenbacker, C. F., and McCoy, K. F. 2009. Feature selection for reference generation as informed by psycholinguistic research. In Proceedings of the CogSci 2009 Workshop on the Production of Referring Expressions: Bridging the Gap between Computational and Empirical Approaches to Reference (PRE-CogSci 2009).Google Scholar
Grice, H. P. 1975. Logic and conversation. In Cole, P. and Morgan, J. L. (eds.), Syntax and Semantics, Volume 3: Speech Acts, pp. 43–58. New York: Academic Press.Google Scholar
Grosz, B. J., Joshi, A. K., and Weinstein, S. 1995. Centering: a framework for modeling the local coherence of discourse. Computational Linguistics 21: 203–225.Google Scholar
Grosz, B. J., and Sidner, C. L. 1986. Attention, intentions, and the structure of discourse. Computational Linguistics 12 (3): 175–204.Google Scholar
Guhe, M. 2009 Generating referring expressions with a cognitive model. In Proceedings of the CogSci 2009 Workshop on the Production of Referring Expressions: Bridging the Gap between Computational and Empirical Approaches to Reference (PRE-CogSci 2009).Google Scholar
Guhe, M., and Bard, E. G. 2008. Adapting referring expressions to the task environment. In Proceedings of the 30th Annual Conference of the Cognitive Science Society. pp. 2404–2409. Austin, TX.Google Scholar
Gundel, J. K., Hedberg, N. and Zacharski, R. 1993. Cognitive status and the form of referring expressions. Language 68: 274–307.CrossRefGoogle Scholar
Hajičová, E. 1993. Issues of Sentence Structure and Discourse Patterns. Prague, Czech Republic: Charles University Press.Google Scholar
Hajičová, E., Sgall, P. and Havelka, J. 2003. Discourse semantics and the salience of referents. Journal of Slavic Language: 127–140.Google Scholar
Hone, K. S., and Graham, R. 2000. Towards a tool for the subjective assessment of speech system intefaces (SASSI). Natural Language Engineering 6 (3–4): 287–303.CrossRefGoogle Scholar
Kittredge, R. and Lehrberger, J. 1982. Sublanguage: Studies of Languages in Restricted Semantic Domains. New York: Walter de Gruyter.CrossRefGoogle Scholar
Krahmer, E. and Theune, M. 2002. Efficient context-sensitive generation of referring expressions. In van Deemter, K. and Kibble, R. (eds.), Information Sharing: Givenness and Newness in Language Processing, pp. 223–264. Stanford, CA: CSLI Publications.Google Scholar
Krauss, R. M., and Weinheimer, S. 1964. Changes in reference phrases as a function of frequency of usage in social interaction: a preliminary study. Psychonomic Science 1: 113–114.CrossRefGoogle Scholar
Krauss, R. M., and Weinheimer, S. 1966. Concurrent feedback, confirmation and the encoding of referents in verbal communication. Journal of Personality and Social Psychology 4: 343–346.CrossRefGoogle ScholarPubMed
Krauss, R. M., and Weinheimer, S. 1967. Effects of referent similarity and communication mode on verbal encoding. Journal of Verbal Learning and Verbal Behavior 6: 359–363.CrossRefGoogle Scholar
Levinson, S. 2000. Presumptive Meanings: The Theory of Generalized Conversational Implicature. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Miller, G. A. 1956. The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review 63: 81–97.CrossRefGoogle ScholarPubMed
Norman, D. A., and Bobrow, D. G. 1975. On data-limited and resource-limited processes. Cognitive Psychology 7: 44–64.CrossRefGoogle Scholar
O'Brien, S. 2003. Controlling controlled english: an analysis of several controlled language rule sets. In Proceedings of the Joint Conference combining the 8th International Workshop of the European Association for Machine Translation and the 4th Controlled Language Applications Workshop (EAMT-CLAW 2003).Google Scholar
Olson, D. 1970. Language and thought. Aspects of a cognitive theory of semantics. Psychological Review 77: 257–273.CrossRefGoogle ScholarPubMed
Papineni, K., Roukos, S., Ward, T., and Zhu, W. J. 2002. BLEU: a method for automatic evaluation of machine translation. In 40th Annual meeting of the Association for Computational Linguistics (ACL), pp. 311–318. Philadelphia, PA, USA.Google Scholar
Paraboni, I., Van Deemter, K., and Masthoff, J. 2007. Generating referring expressions: Making referents easy to identity. Computational Linguistics 33 (2).CrossRefGoogle Scholar
Pechmann, T. 1989. Incremental speech production and referential overspeciification. Linguistics 27: 89–110.CrossRefGoogle Scholar
Pierrehumbert, J. and Hirschberg, J. 1990. The meaning of intonational contours in the interpretation of discourse. In Cohen, P. R., Morgan, J. and Pollack, M. E. (eds.), Intentions in Communication, pp. 271–311. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Reiter, E., and Belz, A. 2009. An investigation into the validity of some metrics for automatically evaluating natural language generation systems. Computational Linguistics 35 (4): 529–558.CrossRefGoogle Scholar
Reiter, E. and Dale, R. 2000. Building Natural Language Generation Systems, pp. 144–158. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Reiter, E., Sripada, S., Hunter, J., Yu, J., and Davy, I. 2005. Choosing words in computer-generated weather forecasts. Artificial Intelligence 167: 137–169.CrossRefGoogle Scholar
Reuther, U. 2003. Two in one – Can it work? Readability and translatability by means of controlled language. In Proceedings of the Joint Conference combining the 8th International Workshop of the European Association for Machine Translation and the 4th Controlled Language Applications Workshop (EAMT-CLAW 2003).Google Scholar
Rantanen, E. M., and Kokayeff, N. K. 2002. Pilot error in copying air traffic control clearances. In Proceedings of the 46th Annual Meeting of the Human Factors and Ergonomics Society.CrossRefGoogle Scholar
Rossion, B., and Pourtois, G. 2001. Revisiting Snodgrass and Vanderwart's object database: color and texture improve object recognition. Journal of Vision 1 (3): 413, 413a.CrossRefGoogle Scholar
Schneiderman, B. 1980. Natural vs. Precise concise language for operation of computers: Research issues and experimental approaches. In Annual Meeting of the Association of Computing Machinery (ACL), pp. 139–141, Philadelphia, PA, USA.Google Scholar
Sidner, C. L., and Forlines, C. 2002. Subset languages for conversing with collaborative interface agents. In Proceedings of the 7th International Conference on Spoken Language Processing (ICSLP), pp. 281–284, Denver, CO, USA.Google Scholar
Snodgrass, J. G., and Vanderwart, M. 1980. A standardized set of 260 pictures: norms for name agreement, image agreement, familiarity, and visual complexity. Journal of Experimental Psychology: Human Learning and Memory 6: 174–215.Google ScholarPubMed
Toth, A. R., Harris, T. K., Sanders, J., Shriver, S., and Rosenfeld, R. 2002. Towards every-citizen's speech interface: an application generator for speech interfaces to databases. In Proceedings of the 7th International Conference on Spoken Language Processing (ICSLP), pp. 1497–1500, Denver, CO, USA.Google Scholar
van der Sluis, I., and Krahmer, E. 2007. Generating multimodal references. Discourse Processes 44 (3): 145–174.CrossRefGoogle Scholar
Viethen, J., and Dale, R. 2006. Algorithms for generating referring expressions: do they do what people do? In Proceedings of the 4th International Conference on Natural Language Generation, pp. 63–70, Sydney, Australia.Google Scholar
Viethen, J., Zwarts, S., Dale, R., and Guhe, M. 2010. Generating subsequent referring expressions in a visual domain. In Proceedings of the 7th Language Resources and Evaluation Conference (LREC). Malta.Google Scholar
Walker, M. A., Joshi, A. K., and Prince, E. 1998. Centering Theory in Discourse. Oxford, UK: Oxford University Press.Google Scholar
Walker, M. A., Litman, D. J., Kamm, C. A., and Abella, A. 1998 Evaluating spoken dialogue agents with PARADISE: two case studies. Computer Speech and Language 12–3.Google Scholar