The Trend towards Statistical Models in Natural Language Processing

  • Mark Y. Liberman
Part of the ESPRIT Basic Research Series book series (ESPRIT BASIC)

Abstract

Over the past few years, we have seen a significant increase in the number and sophistication of computational studies of large bodies of text and speech. Such studies have a wide variety of topics and motives, from lexicography and studies of language change, to methods for automated indexing and information retrieval, tagging and parsing algorithms, techniques for generating idiomatic text, cognitive models of language acquisition, and statistical models for application in speech recognizers, text or speech compression schemes, optical character readers, machine translation systems, and spelling correctors.

Keywords

Speech Recognition Natural Language Processing Spelling Corrector Speech Recognizer Language Change 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    ACL: 1989, ‘ACL Data Collection Initiative Announcement’, The Finite String 15.Google Scholar
  2. 2.
    Bahl, L.B., Brown, P.F., de Souza, P.V., and Mercer, R.L.: 1990, ‘A Tree-Based Statistical Language Model for Natural Language Speech Recognition’. In Waibel, A., and Lee, K.-F., Readings in Speech Recognition, San Mateo, CA: Morgan Kaufman.Google Scholar
  3. 3.
    Brill, E., Magerman, D., Marcus, M., and Santorini, B.: 1990, ‘Deducing Linguistic Structure from the Statistics of Large Corpora’. In Proceedings of the DARPA Speech and Natural Language Workshop, New York: Morgan Kaufman.Google Scholar
  4. 4.
    Brown, P.F., Delia Pietra, S.A., Delia Pietra, V.J., Lai, J.C., Mercer, R.L.: 1990, ‘An Estimate of an Upper Bound for the Entropy of English’. Ms.Google Scholar
  5. 5.
    Brown, P.F., Cocke J., Delia Pietra, S.A., Delia Pietra, V.J., Jelinek, F., Lafferty, J.D., Mercer, R.L., and Roosin, P.S.: 1990, ‘A Statistical Approach to Machine Translation’. Computational Linguistics 16, 79–85.Google Scholar
  6. 6.
    Chitrao, M., and Grishman, R.: 1990, ‘Statistical Parsing of Messages’. In Proceedings of DARPA Speech and Natural Language Processing Workshop. New York: Morgan Kaufman.Google Scholar
  7. 7.
    Chomsky, N.: 1957, Syntactic Structures. The Hague: Mouton.Google Scholar
  8. 8.
    Choueka, Y.: 1988, ‘Looking for Needles in a Haystack: Or, Locating Interesting Collocational Expressions in Large Textual Databases. In Proceedings of the RIA088 Conference on User-Oriented Content-Based Text and Image Handling. Cambridge, MA.Google Scholar
  9. 9.
    Church, K.W.: 1988, ‘A Stochastic Parts Program and Noun Phrase Parser for Unrestricted Text’. In Proceedings of the Second ACL Conference on Applied Natural Language Processing. Austin, Texas.Google Scholar
  10. 10.
    Church, K.W. and Hanks, P.: 1990, ‘Word Association Norms, Mutual Information and Lexicography’. Computational Linguistics 16, 22–29.Google Scholar
  11. 11.
    Church, K.W., Hanks, P., and Hindle, D.: forthcoming, ‘Using Statistics in Lexical Analysis’. In Zernik, V., ed. Lexical Acquisition: Using On-line Resources to Build a Lexicon.Google Scholar
  12. 12.
    Dagan, I., and Itai, A.: 1991 ‘A Statistical Filter for Resolving Pronoun References’. In Proceedings of the 29th Meeting of the ACL, Berkeley.Google Scholar
  13. 13.
    Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K., and Harshman, R.: 1990, ‘Indexing by Latent Semantic Analysis’. Journal of the American Society for Information Science.Google Scholar
  14. 14.
    De Marcken, C.G.: 1990, ‘Parsing the LOB Corpus’. In Proceedings of the 28th Annual Meeting of the ACL, Pittsburgh, PA, 243-251.Google Scholar
  15. 15.
    DeRose, S.J.: 1988, ‘Grammatical Category Disambiguation by Statistical Optimization’. Computational Linguistics 14, 31–39.Google Scholar
  16. 16.
    Fillmore, C.J., and Atkins, B.T.: forthcoming, ‘Toward a Frame-Based Lexicon: the Semantics of RISK and Its Neighbors’. In Lehrer, A., and Kittay, E. (eds.) Papers in Lexical Semantics.Google Scholar
  17. 17.
    Gale, W.A. and Church, K.W.: 1990, ‘Poor Estimates of Context Are Worse than None’. In Proceedings of the DARPA Speech and Natural Language Workshop, June 1990.Google Scholar
  18. 18.
    Hanson, S. J. and Kegl, J.: 1987, ‘PARSNIP: A Connectionist Network That Learns Natural Language Grammar from Exposure to Natural Language Sentences’. In Proceedings of the Cognitive Science Society, Seattle, WA, 106-119.Google Scholar
  19. 19.
    Hindle, D.: 1990, ‘Noun Classification from Predicate-Argument Structures’. In Proceedings of the 28th Annual Meeting of the ACL, Pittsburgh, PA, 268-275.Google Scholar
  20. 20.
    Hindle, D. and Rooth., M.: 1990,’ structural Ambiguity and Lexical Relations’. In Proceedings of the DARPA Speech and Natural Language Workshop. June 1990.Google Scholar
  21. 21.
    Jelinek, F.: 1990, ‘Self-Organized Language Modeling for Speech Recognition’. In Waibel, A., and Lee, K.-F. (eds.), Readings in Speech Recognition, San Mateo, CA: Morgan Kaufman.Google Scholar
  22. 22.
    Jelinek, F., Lafferty, J.D., and Mercer, R.L.: 1990, Basic Methods of Probabilistic Context Free Grammars. Yorktown Heights: IBM RC 16374 (#72684).Google Scholar
  23. 23.
    Jelinek, F. and Mercer, R.: 1980, ‘Interpolated Estimation of Markov Source Parameters from Sparse Data’. In Proceedings of the Workshop on Pattern Recognition in Practice. Amsterdam: North-Holland.Google Scholar
  24. 24.
    Johansson, S., Atwell, E., Garside, R., and Leech, G.: 1986, The Tagged LOB Corpus: User’s Manual. Bergen: Norwegian Computing Centre for the Humanities.Google Scholar
  25. 25.
    Kernighan, M.D., Church, K.W., and Gale, W.A.: 1990, ‘A Spelling Corrector Based on Error Frequencies’. In Proceedings of the Thirteenth International Conference on Computational Linguistics.Google Scholar
  26. 26.
    Kroch, A.: 1989 ‘Function and Grammar in the History of English: Periphrastic Do’. In Fasold, R., and Schiffrin, D. (eds.), Language Change and Variation. Amsterdam and Philadelphia: John Benjamins.Google Scholar
  27. 27.
    Kucera, H. and Francis, W.N.: 1967, Computational Analysis of Present-Day American English. Providence: Brown University Press.Google Scholar
  28. 28.
    Liberman, M.: 1989, ‘Text on Tap: the ACL/DCI’. In Proceedings of the DARPA Speech and Natural Language Workshop, October 1989. San Mateo, CA.: Morgan Kaufmann.Google Scholar
  29. 29.
    Miller, G.A., and Chomsky, N.: 1963, ‘Finitary Models of Language Users’. In Luce, R.D., Bush, R.R., and Galanter, E. (eds.), Handbook of Mathematical Psychology. Vol. 2, 419–492. Wiley.Google Scholar
  30. 30.
    Partee, B., Ter Meulen, A., and Wall, W.: 1990, Mathematical Methods in Linguistics. Dordrecht: Reidel.MATHCrossRefGoogle Scholar
  31. 31.
    Shannon, C.: 1951, ‘Prediction and Entropy of Printed English’, Bell Systems Technical Journal 30, 50–64.MATHGoogle Scholar
  32. 32.
    Sinclair, J.M. (ed.): 1987, Looking Up: An Account of the COBUILD Project in Lexical Computing. London and Glasgow: Collins.Google Scholar
  33. 33.
    Smadja, F.: 1989, ‘Macrocoding the Lexicon with Co-occurrence Knowledge’. In Proceedings of the First International Lexical Acquisition Workshop, IJCAI, Detroit, August 1989.Google Scholar
  34. 34.
    Smadja, F. and McKeown, K.: 1990, ‘Automatically Extracting and Representing Collocations for Language Generation’. In Proceedings of the 28th Annual Meeting of the ACL, Pittsburgh, PA, 252-259.Google Scholar
  35. 35.
    Srihari, S.N.: 1984, Computer Text Recognition and Error Correction. IEEE Computer Society Press.Google Scholar
  36. 36.
    Walker, D.: 1989, ‘Developing Lexical Resources’. In Proceedings of the 5th Annual Conference of the UW Centre for the New Oxford English Dictionary, Waterloo, Ontario.Google Scholar

Copyright information

© ECSC - EEC - EAEC, Brussels - Luxembourg 1991

Authors and Affiliations

  • Mark Y. Liberman
    • 1
  1. 1.Department of Computer and Information ScienceUniversity of PennsylvaniaUSA

Personalised recommendations