171
Views
12
CrossRef citations to date
0
Altmetric
Original Articles

Probabilistic reference and grounding with PRAGR for dialogues with robots

, &
Pages 889-911 | Received 04 Dec 2014, Accepted 11 Feb 2016, Published online: 11 Apr 2016

References

  • Arkin, M., Chew, L. P., Huttenlocher, D. P., Kedem, K., & Mitchell, J. S. B. (1991). An efficiently computable metric for comparing polygonal shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 13, 206–209.
  • Canny, J. F. (1986). A computational approach to edge detection. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 8, 679–697.
  • Carlson, L., & Covey, E. (2005). How far is near? inferring distance from spatial descriptions. Language and Cognitive Processes, 20, 617–632.
  • Chang, M.-W., Ratinov, L., & Roth, D. (2012). Structured learning with constrained conditional models. Machine Learning, 88, 399–431.
  • Clark, H. H., & Brennan, S. E. (1991). Grounding in communication. Perspectives on Socially Shared Cognition, 13, 127–149.
  • Clark, H. H., & Wilkes-Gibbs, D. (1986). Referring as a collaborative process. Cognition, 22, 1–39.
  • Dale, R. (1989). Cooking up referring expressions. In Proceedings of the 27th annual meeting on Association for Computational Linguistics (pp. 68–75) Vancouver.
  • Dale, R. (1992). Generating referring expressions: Constructing descriptions in a domain of objects and processes. Cambridge, MA: MIT Press.
  • Dale, R., & Reiter, E. (1995). Computational interpretations of the gricean maxims in the generation of referring expressions. Cognitive Science, 18, 233–263.
  • Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the em algorithm. Journal of the royal statistical society. Series B (methodological), 39, 1–38.
  • Eyre, H., & Lawry, J. (2014). Language games with vague categories and negations. Adaptive Behavior, 22, 289–303.
  • Falomir, Z., Gonzalez-Abril, L., Museros, L., & Ortega, J. (2013). Measures of similarity between objects from a qualitative shape description. Spatial Cognition and Computation, 13, 181–218.
  • Falomir, Z., Museros, L., & Gonzalez-Abril, L. (2015). A model for colour naming and comparing based on conceptual neighbourhood. An application for comparing art compositions. Knowledge-based Systems, 81, 1–21.
  • Falomir, Z., Museros, L., Gonzalez-Abril, L., & Sanz, I. (2013). A model for qualitative colour comparison using interval distances. Displays, 34, 250–257.
  • Gapp, K. P. (1995). An empirically validated model for computing spatial relations. In Proceedings of KI-95. Berlin: Springer.
  • Gärdenfors, P. (2004). Conceptual spaces: The geometry of thought. Cambridge, MA: A Bradford book, MIT Press.
  • Gorniak, P., & Roy, D. (2004). Grounded semantic composition for visual scenes. Journal of Artificial Intelligence Research, 21, 429–470.
  • Gottfried, B. (2008). Qualitative similarity measures: The case of two-dimensional outlines. Computer Vision and Image Understanding, 110, 117–133.
  • Grice, H. P. (1975). Logic and conversation. In P.Cole & J. L. Morgan (Eds.), Speech acts. Vol. 3 of Syntax and semantics (pp. 43–58). New York, NY: Academic Press.
  • Hermann, T. (1990). Vor, hinter, rechts und links: das 6H-Modell. psychologische studien zum sprachlichen lokalisieren [in front of, behind, left and right: the 6H-Model. psychological studies in verbal localisation]. Zeitschrift für Literaturwissenschaft und Linguistik, 20, 117–140.
  • Hermann, T., & Laucht, M. (1976). On multiple verbal codability of objects. Psychological Research, 38, 355–368.
  • Horacek, H. (2005). Generating referential descriptions under conditions of uncertainty. In Proceedings of the 10th European Workshop on Natural Language Generation (ENLG) (pp. 58–67). Aberdeen.
  • Kelleher, J. D. (2011). Visual salience and the other one. Salience: Multidisciplinary Perspectives on Its Function in Discourse, 227, 205–231.
  • Kelleher, J. D., & Kruijff, G.-J. (2005). A context-dependent algorithm for generating locative expressions in physically situated environments. In C. Mellish, E. Reiter, K. Jokinen, & G. Wilcock (Eds.), Proceedings of the 10th European Workshop on Natural Language Generation. Aberdeen: SIGGEN, ACL.
  • Koolen, R., Gatt, A., Goudbeek, M., & Krahmer, E. (2011). Factors causing overspecification in definite descriptions. Journal of Pragmatics, 43, 3231–3250.
  • Krahmer, E., & van Deemter, K. (2012). Computational generation of referring expressions: A survey. Computational Linguistics, 38, 173–218.
  • Latecki, L. J., & Lakaemper, R. (2000). Shape similarity measure based on correspondence of visual parts. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 22, 1185–1190.
  • Latecki, L. J., Lakaemper, R., & Eckhardt, U. (2000). Shape descriptors for non-rigid shapes with a single closed contour. In Proceedings of Computer Vision and Pattern Recognition conference (CVPR) (pp. 424–429). Hilton Head Island, SC
  • Latecki, L. J., Lakaemper, R., & Wolter, D. (2005). Optimal partial shape similarity. Image and Vision Computing, 23, 227–236.
  • Lawry, J., & Tang, Y. (2009). Uncertainty modelling for vague concepts: A prototype theory approach. Artificial Intelligence, 173, 1539–1558.
  • Levinson, S. C. (1996). Frames of reference and molyneux question: Cross-linguistic evidence. In P. Bloom, M. Peterson, L. Nadel, & M. Garrett (Eds.), Language and space (pp. 109–169). Cambridge, MA: MIT Press.
  • Ling, H., & Jacobs, D. W. (2007). Shape classification using the inner-distance. IEEE Transactions on Pattern Analysis and Machine Intelligence, 29, 286–299.
  • Macrini, D., Siddiqi, K., & Dickinson, S. J. (2008). From skeletons to bone graphs: Medial abstraction for object recognition. In Proceedings of Computer Vision and Pattern Recognition conference (CVPR). Anchorage, AK: IEEE Computer Society.
  • Mast, V., Couto Vale, D., Falomir, Z., & Elahi, M. F. (2014). Referential grounding for situated human-robot communication. In V. Rieser & P. Muller (Eds.), Proceedings of SemDial 2014 -- DialWatt (pp. 223–225). Edinburgh.
  • Mast, V., & Wolter, D. (2013a, July). Context and vagueness in REG. In Proceedings of PRE-CogSci 2013. Berlin.
  • Mast, V., & Wolter, D. (2013b, October). A probabilistic framework for object descriptions in indoor route instructions. In T. Tenbrink, J. Stell, A. Galton, & Z. Wood (Eds.), Spatial information theory. Vol. 8116 of Lecture Notes in Computer Science, Scarborough (pp. 185–204). Berlin: Springer International Publishing.
  • Mast, V., Wolter, D., Klippel, A., Wallgrün, J. O., & Tenbrink, T. (2014). Boundaries and prototypes in categorizing direction. In Spatial cognition IX (pp. 92–107). Bremen.
  • Menegaz, G., Troter, A. L., Sequeira, J., & Boi, J. M. (2007). A discrete model for color naming. EURASIP Journal on Applied Signal Processing. Special Issue on Image Perception, 2007(1), 1–10.
  • Meo, T., McMahan, B., & Stone, M. (2014). Generating and resolving vague color references. In V. Rieser & P. Muller (Eds.), Proceedings of SemDial 2014/DialWatt (pp. 107–115). Edinburgh
  • Moratz, R., & Tenbrink, T. (2006). Spatial reference in linguistic human-robot interaction: Iterative, empirically supported development of a model of projective relations. Spatial Cognition and Computation, 6, 63–106.
  • Mori, G., Belongie, S., & Malik, J. (2001). Shape contexts enable efficient retrieval of similar shapes. In Proceedings of Computer Vision and Pattern Recognition conference (CVPR) (pp. 723–730). Kauai, HI: IEEE Computer Society.
  • Palmer, S. E. (1999). Vision science: Photons to phenomenology. Cambridge, MA: MIT Press.
  • Palmer, S. E., & Schloss, K. B. (2010). An ecological valence theory of human color preference. Proceedings of the National Academy of Sciences, 107, 8877–8882.
  • Pechmann, T. (1989). Incremental speech production and referential overspecification. Linguistics, 27, 89–110.
  • Perera, I., & Allen, J. F. (2015). Quantity, contrast, and convention in cross-situated language comprehension. In CoNLL 2015 (p. 226). Beijing.
  • Regier, T., & Carlson, L. A. (2001). Grounding spatial language in perception: An empirical and computational investigation. Journal of Experimental Psychology: General, 130, 273–298.
  • Reiter, E. (1990). The computational complexity of avoiding conversational implicatures. In Proceedings of the 28th annual meeting on Association for Computational Linguistics (pp. 97–104). Stroudsburg, PA.
  • Reiter, E., & Dale, R. (1992). A fast algorithm for the generation of referring expressions. In Proceedings of the 14th conference on Computational linguistics-Volume 1, Association for Computational Linguistics (pp. 232–238). Stroudsburg, PA.
  • Sarifuddin, M., & Missaoui, R. (2005). A new perceptually uniform color space with associated color similarity measure for content-based image and video retrieval. In Multimedia information retrieval workshop, 28th annual ACM SIGIR conference (pp. 3–7). Salvador, Brazil.
  • Seaborn, M., Hepplewhite, L., & Stonham, T. J. (2005). Fuzzy colour category map for the measurement of colour similarity and dissimilarity. Pattern Recognition, 38, 165–177.
  • Sebastian, T. B., Klein, P. N., & Kimia, B. B. (2002). Shock-based indexing into large shape databases. In 7th European Conference on Computer Vision (ECCV) (pp. 731–746). London: Springer-Verlag.
  • Soto-Hidalgo, J. M., Chamorro-Martínez, J., & Sanchez, D. (2010, July). A new approach for defining a fuzzy color space. In 2010 IEEE International Conference on Fuzzy Systems (FUZZ) (pp. 1–6). Barcelona, Spain.
  • Spranger, M., & Pauw, S. (2012). Dealing with perceptual deviation -- Vague semantics for spatial language and quantification. In L. Steels & M. Hild (Eds.), Language grounding in robots (pp. 173–192). Berlin: Springer
  • Super, B. (2004). Fast correspondence-based system for shape retrieval. Pattern Recognition Letters, 25, 217–225.
  • Tellex, S., Knepper, R., Li, A., Rus, D., & Roy, N. (2014). Asking for help using inverse semantics. In Proceedings of robotics: Science and systems. Berkeley, CA.
  • Tellex, S., Kollar, T., Dickerson, S., Walter, M., Banerjee, A., Teller, S., & Roy, N. (2011). Understanding natural language commands for robotic navigation and mobile manipulation. In Proceedings of AAAI. San Francisco, CA.
  • van Deemter, K. (2006). Generating referring expressions that involve gradable properties. Computational Linguistics, 32, 195–222.
  • Zimmer, H., Speiser, H., Baus, J., Blocher, A., & Stopp, E. (1998). The use of locative expressions in dependence of the spatial relation between target and reference object in two-dimensional layouts. In C. Freksa, C. Habel, & K. Wender (Eds.), Spatial cognition: An inderdisciplinary approach to representing and processing spatial knowledge. Vol. 1404 of Lecture Notes in Computer Science (pp. 223–240). Berlin: Springer.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.