Abstract
This paper presents a method for inferring reversible attribute grammars from tagged natural language sentences. Attribute grammars are a form of augmented context free grammar that assign “meaning” in the form of a data structure to a string in a context free language. The method presented in this paper has the ability to infer attribute grammars that can generate a wide range of useful data structures such as simple and structured types, lists, concatenated strings, and natural numbers. The method also presents two new forms of grammar generalisation; generalisation based upon identification of optional phrases and generalisation based upon lists. The method has been applied to and tested on the task of the rapid development of spoken dialog systems.
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References
Knuth, Donald E., 1968, “Semantics of context-free languages.” Mathematical Systems Theory, 2(2): pp 127–45.
Starkie, Bradford C, 2001. Programming Spoken Dialogs Using Grammatical Inference, in AI 2001: Advances in Artificial Intelligence, 14 th Australian Joint Conference on Artificial Intelligence, pp 449–460, Berlin: Springer Verlag
Stolcke, Andreas, 1994, Bayesian Learning of Probabilistic Language Models. Berkely CA: Univeristy of California dissertation.
Stolcke, A. and Omohundro, S. 1994, Inducing probabilistic grammars by Bayesian model merging, Grammatical Inference and Applications. Second International Colloquium on Grammatical Inference, ICGI-94, pp 106–18 Berlin: Springer Verlag.
Cancedda, Nicola and Samuelsson, 2000, “Corpus-Based Grammar Specialization”, Proceedings of the 4th conference on Computational Natural Language Learning and of the Second Learning Language in Logic Workshop, pp 7–12, Association for Computational Linguistics, New Brunswick USA.
Alexin Z., Gyimóthy T., and Boström H., 1997, IMPUT: An interactive learning tool based on program specialization. Intelligent Data Analysis, 1(4), October 1997. Elsevier Science Inc
Samuelsson, Christer & Rayner, Manny, 1991, Quantitative evaluation of explanation based learning as an optimization tool for a large-scale natural language system. In Proceedings of the IJCAI-91, Sydney Australia.
Pearlman J., 2000, “SLS-Lite: Enabling Spoken Language Design for non experts”, M.Eng. Thesis, MIT, Cambridge, 2000.
Charniak, Eugene1993, Statistical Language Learning, Cambridge, Mass.: MIT Press.
Starkie, Bradford C, 1999. A method of developing an interactive system, International Patent WO 00/78022.
Salton, Gerard & McGill, Michael J, 1983, Introduction to Modern Information Retrieval, p55, McGraw-Hill Inc. TM-Trade mark applied for by Telstra New Wave Pty Ltd.
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Starkie, B. (2002). Inferring Attribute Grammars with Structured Data for Natural Language Processing. In: Adriaans, P., Fernau, H., van Zaanen, M. (eds) Grammatical Inference: Algorithms and Applications. ICGI 2002. Lecture Notes in Computer Science(), vol 2484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45790-9_19
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DOI: https://doi.org/10.1007/3-540-45790-9_19
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