Learning to connect language and perception

Proceedings of the National Conference on Artificial Intelligence

Volumn 3, Issue , 2008, Pages 1598-1601

  Mooney, Raymond J ^a  

^a University of Texas at Austin   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONCERTED EFFORTS; FUTURE RESEARCHES; IMPORTANT DIRECTIONS; MACHINE LEARNINGS; NATURAL LANGUAGE PROCESSING; PROBABILISTIC KNOWLEDGES;

ARTIFICIAL INTELLIGENCE; BIONICS; COMPUTATIONAL LINGUISTICS; COMPUTER VISION; EDUCATION; IMAGE PROCESSING; INTELLIGENT SYSTEMS; LEARNING SYSTEMS; LINGUISTICS; VISUAL COMMUNICATION;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 57749107432     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (35)

1. Aggarwal, J. K., and Park, S. 2004. Human motion: Modeling and recognition of actions and interactions. In Proceedings of the 2nd International Symposium on 3D Data Processing, Visualization, and Transmission.
2. André, E.; Binsted, K.; Tanaka-Ishii, K.; Luke, S.; Herzog, G.; and Rist, T. 2000. Three RoboCup simulation league commentator systems. Al Magazine 21(1):57-66.
3. Bakir, G.; Hoffman, T.; Schölkopf, B.; Smola, A. I.; Taskar, B.; and Vishwanathan, S. V. N., eds. 2007. Predicting Structured Data. Cambridge, MA: MIT Press.
4. Barnard, K., and lohnson, M. 2005. Word sense disambiguation with pictures. Artificial Intelligence 167:13-30.
5. Barnard, K.; Duygulu, P.; Forsyth, D.; de Freitas, N.; Blei, D. M.; and lordan, M. I. 2003. Matching words and pictures. Journal of Machine Learning Research 3:1107-1135.
6. Bekkerman, R., and leon, J. 2007. Multi-modal clustering for multimedia collections. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
7. Bloom, P. 2000. How Children Learn the Meanings of Words. Cambridge, MA: MIT Press.
8. Chen, D. L., and Mooney, R. J. 2008. Learning to sportscast: A test of grounded language acquisition. In Proceedings of 25th International Conference on Machine Learning (ICML-2008).
9. Chiang, D. 2005. A hierarchical phrase-based model for statistical machine translation. In Proceedings of the 43nd Annual Meeting of the Association for Computational Linguistics (ACL-05), 263-270.
10. Dietterich, T. G.; Lathrop, R. H.; and Lozano-Perez, T. 1997. Solving the multiple instance problem with axis-parallel rectangles. Artificial Intelligence 89(l-2):31-71.
11. Feldman, J. A.; Lakoff, G.; Bailey, D. R.; Narayanan, S.; Regier, T.; and Stolcke, A. 1996. L0 - the first five years of an automated language acquisition project. AI Review 8.
12. Fern, A.; Givan, R.; and Siskind, J. M. 2002. Specific-to-general learning for temporal events with application to learning event definitions from video. Journal of Artificial Intelligence Research 17:379-449.
13. Fleischman, M., and Roy, D. 2005. Intentional context in situated natural language learning. In Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL-2005), 104-111.
14. Fleischman, M., and Roy, D. 2007. Situated models of meaning for sports video retrieval. In Proceedings of Human Language Technologies: The Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT-07).
15. Ge, R., and Mooney, R. J. 2005. A statistical semantic parser that integrates syntax and semantics. In Proceedings of the Ninth Conference on Computational Natural Language Learning (CoNLL-2005), 9-16.
16. Gorniak, P., and Roy, D. 2005. Speaking with your sidekick: Understanding situated speech in computer role playing games. In Proceedings of the 4th Conference on Artificial Intelligence and Interactive Digital Entertainment.
17. Harnad, S. 1990. The symbol grounding problem. Physica D 42:335-346.
18. Kate, R. J., and Mooney, R. J. 2006. Using string-kernels for learning semantic parsers. In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (COLING/ACL-06), 913-920.
19. Kate, R. J., and Mooney, R. J. 2007. Learning language semantics from ambiguous supervision. In Proceedings of the Twenty-Second Conference on Artificial Intelligence (AAAI-2007), 895-900.
20. Lakoff, G., and Johnson, M. 1980. Metaphors We Live By. Chicago: University Of Chicago Press.
21. Lodhi, H.; Saunders, C.; Shawe-Taylor, J.; Cristianini, N.; and Watkins, C. 2002. Text classification using string kernels. Journal of Machine Learning Research 2:419-444.
22. Manning, C. D., and Schütze, H. 1999. Foundations of Statistical Natural Language Processing. Cambridge, MA: MIT Press.
23. Ray, S., and Craven, M. 2005. Supervised versus multiple instance learning: An empirical comparison. In Proceedings of 22nd International Conference on Machine Learning (ICML-2005), 697-704.
24. Roy, D. K., and Pentland, A. P. 2002. Learning words from sights and sounds: a computational model. Cognitive Science 26:113-146.
25. Roy, D. 2002. Learning visually grounded words and syntax for a scene description task. Computer Speech and Language 16(3):353-385.
26. Roy, D. 2005. Grounding words in perception and action: Insights from computational models. Trends in Cognitive Science 9(8):389-396.
27. Sebe, N.; Cohen, I.; Garg, A.; and Huang, T. 2005. Machine Learning in Computer Vision. Berlin: Springer Ver-lag.
28. Siskind, J. M. 1996. A computational study of cross-situational techniques for learning word-to-meaning mappings. Cognition 61(1 ):39-91.
29. Wong, Y., and Mooney, R. J. 2006. Learning for semantic parsing with statistical machine translation. In Proceedings of Human Language Technology Conference /North American Chapter of the Association for Computational Linguistics Annual Meeting (HLT-NAACL-06), 439-446.
30. Wong, Y., and Mooney, R. J. 2007a. Generation by inverting a semantic parser that uses statistical machine translation. In Proceedings of Human Language Technologies: The Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT-07), 172-179.
31. Wong, Y, and Mooney, R. J. 2007b. Learning synchronous grammars for semantic parsing with lambda calculus. In Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL-07), 960-967.
32. Wu, D. 1997. Stochastic inversion transduction grammars and bilingual parsing of parallel corpora. Computational Linguistics 23(3):377-403.
33. Yu, C, and Ballard, D. H. 2004. On the integration of grounding language and learning objects. In Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI-2004), 488-493.
34. Zelle, J. M., and Mooney, R. J. 1996. Learning to parse database queries using inductive logic programming. In Proceedings of the Thirteenth National Conference on Artificial Intelligence (AAAI-96), 1050-1055.
35. Zettlemoyer, L. S., and Collins, M. 2005. Learning to map sentences to logical form: Structured classification with probabilistic categorial grammars. In Proceedings of 21th Conference on Uncertainty in Artificial Intelligence (UAI-2005).