1932

Abstract

In this review, I assess a variety of constraint-based formal frameworks that can treat variable phenomena, such as well-formedness intuitions, outputs in free variation, and lexical frequency-matching. The idea behind this assessment is that data in gradient linguistics fall into natural mathematical patterns, which I call . The key signatures treated here are the , going from zero to one probability, and the , which combines two or more sigmoids. I argue that these signatures appear repeatedly in linguistics, and I adduce examples from phonology, syntax, semantics, sociolinguistics, phonetics, and language change. I suggest that the ability to generate these signatures is a trait that can help us choose between rival frameworks.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-linguistics-031220-013128
2022-01-14
2025-06-20
Loading full text...

Full text loading...

/deliver/fulltext/linguistics/8/1/annurev-linguistics-031220-013128.html?itemId=/content/journals/10.1146/annurev-linguistics-031220-013128&mimeType=html&fmt=ahah

Literature Cited

  1. AnderBois S, Brasoveanu A, Henderson R. 2012.. The pragmatics of quantifier scope: a corpus study. . In Proceedings of Sinn und Bedeutung 16, pp. 1528. Cambridge, MA:: MIT Press
    [Google Scholar]
  2. Anttila A. 1997.. Deriving variation from grammar: a study of Finnish genitives. . In Variation, Change and Phonological Theory, ed. F Hinskens, R van Hout, L Wetzels , pp. 3568. Amsterdam:: John Benjamins
    [Google Scholar]
  3. Anttila A, Magri G. 2017.. Does MaxEnt overgenerate? Implicational universals in maximum entropy grammar. . In Proceedings of the 2017 Annual Meeting on Phonology, ed. G Gallagher, M Gouskova, S Heng Yin . Washington, DC:: Linguist. Soc. Am. https://doi.org/10.3765/amp.v5i0.4260
    [Crossref] [Google Scholar]
  4. Anttila A, Magri G, Borgeson S. 2019.. Equiprobable mappings in weighted constraint grammars. . In Proceedings of the 16th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology, ed. G Nicolai, R Cotterell , pp. 12534. Stroudsburg, PA:: Assoc. Comput. Linguist.
    [Google Scholar]
  5. Baayen RH. 2008.. Analyzing Linguistic Data: A Practical Introduction to Statistics Using R. Cambridge, UK:: Cambridge Univ. Press
    [Google Scholar]
  6. Bailey C-JN. 1973.. Variation and Linguistic Theory. Washington, DC:: Cent. Appl. Linguist.
    [Google Scholar]
  7. Battista J, Badcock DR, McKendrick AM. 2011.. Migraine increases centre-surround suppression for drifting visual stimuli. . PLOS ONE 6:(4):e18211
    [Google Scholar]
  8. Beaudot WHA. 1996.. Adaptive spatiotemporal filtering by a neuromorphic model of the vertebrate retina. . In Proceedings of 3rd IEEE International Conference on Image Processing, Vol. 1, pp. 42730. New York:: IEEE
    [Google Scholar]
  9. Berko J. 1958.. The child's learning of English morphology. . Word 14::15077
    [Google Scholar]
  10. Blythe RA, Croft W. 2012.. S-curves and the mechanisms of propagation in language change. . Language 88::269304
    [Google Scholar]
  11. Bod R, Hay J, Jannedy S, eds. 2003.. Probabilistic Linguistics. Cambridge, MA:: MIT Press
    [Google Scholar]
  12. Boersma P. 1998.. Functional Phonology: Formalizing the Interactions Between Articulatory and Perceptual Drives. The Hague, Neth:.: Holland Acad. Graph.
    [Google Scholar]
  13. Boersma P, Pater J. 2016.. Convergence properties of a gradual learning algorithm for Harmonic Grammar. . In Harmonic Grammar and Harmonic Serialism, ed. J McCarthy, J Pater , pp. 389434. London:: Equinox
    [Google Scholar]
  14. Bresnan J, Cueni A, Nikitina T, Baayen RH. 2007.. Predicting the dative alternation. . In Cognitive Foundations of Interpretation, ed. G Boume, I Krämer, J Zwarts , pp. 6994. Amsterdam:: R. Neth. Acad. Sci.
    [Google Scholar]
  15. Bresnan J, Ford M. 2010.. Predicting syntax: processing dative constructions in American and Australian varieties of English. . Language 86::168213
    [Google Scholar]
  16. Bresnan J, Hay J. 2008.. Gradient grammar: an effect of animacy on the syntax of give in New Zealand and American English. . Lingua 118::24559
    [Google Scholar]
  17. Cedergren HJ, Sankoff D. 1974.. Variable rules: performance as a statistical reflection of competence. . Language 50::33355
    [Google Scholar]
  18. Chambers JK, Schilling N, eds. 2013.. The Handbook of Language Variation and Change. Oxford, UK:: Wiley-Blackwell. , 2nd ed..
    [Google Scholar]
  19. Coetzee AW, Kawahara S. 2013.. Frequency biases in phonological variation. . Nat. Lang. Linguist. Theory 31::4789
    [Google Scholar]
  20. Cramer JS. 2002.. The origins of logistic regression. Tinbergen Inst. Discuss. Pap. 02-119/4 , Tinbergen Inst., Amsterdam
    [Google Scholar]
  21. de Lacy P. 2004.. Markedness conflation in Optimality Theory. . Phonology 21::14599
    [Google Scholar]
  22. Ernestus M, Baayen RH. 2003.. Predicting the unpredictable: interpreting neutralized segments in Dutch. . Language 79::538
    [Google Scholar]
  23. Fechner G. 1966 (1860.). Elements of Psychophysics, trans. HE Adler . Amsterdam:: Bonset
    [Google Scholar]
  24. Flemming E, Cho H. 2017.. The phonetic specification of contour tones: evidence from the Mandarin rising tone. . Phonology 34::140
    [Google Scholar]
  25. Ganong F. 1980.. Phonetic categorization in auditory word perception. . J. Exp. Psychol.: Hum. Percept. Perform. 6::11025
    [Google Scholar]
  26. Goldberg Y. 2017.. Neural Network Methods for Natural Language Processing. San Rafael, CA:: Morgan and Claypool
    [Google Scholar]
  27. Goldwater S, Johnson M. 2003.. Learning OT constraint rankings using a Maximum Entropy model. . In Proceedings of the Stockholm Workshop on ‘Variation Within Optimality Theory J Spenader, A Eriksson, Ö Dahl , pp. 11322. Stockholm:: Stockholm Univ.
    [Google Scholar]
  28. Hayes B. 2017.. Varieties of Noisy Harmonic Grammar. . In Proceedings of the 2016 Annual Meeting on Phonology, ed. K Jesney, C O'Hara, C Smith, R Walker . Washington, DC:: Linguist. Soc. Am. https://doi.org/10.3765/amp.v4i0.3997
    [Crossref] [Google Scholar]
  29. Hayes B, Schuh R. 2019.. Metrical structure and sung rhythm of the Hausa rajaz. . Language 95::e25399
    [Google Scholar]
  30. Hayes B, Wilson C. 2008.. A maximum entropy model of phonotactics and phonotactic learning. . Linguist. Inq. 39::379440
    [Google Scholar]
  31. Hayes B, Zuraw K, Siptar P, Londe Z. 2009.. Natural and unnatural constraints in Hungarian vowel harmony. . Language 85::82263
    [Google Scholar]
  32. Irvine A, Dredze M. 2017.. Harmonic Grammar, Optimality Theory, and syntax learnability: an empirical exploration of Czech word order. . arXiv:1702.05793 [cs.CL]
  33. Jäger G. 2007.. Maximum entropy models and Stochastic Optimality Theory. . In Architectures, Rules, and Preferences: Variations on Themes by Joan W. Bresnan, ed. A Zaenen, J Simpson, TH King, J Grimshaw, J Maling, C Manning , pp. 46779. Stanford, CA:: CSLI Publ.
    [Google Scholar]
  34. Jesney K. 2007.. The locus of variation in weighted constraint grammars. Paper presented at the Workshop on Variation, Gradience and Frequency in Phonology , Stanford, CA:, July 6–8
    [Google Scholar]
  35. Johnson DE. 2009.. Getting off the GoldVarb standard: introducing Rbrul for mixed-effects variable rule analysis. . Lang. Linguist. Compass 3::35983
    [Google Scholar]
  36. Johnson K. 2011.. Quantitative Methods in Linguistics. New York:: Wiley
    [Google Scholar]
  37. Jurafsky D. 2003.. Probabilistic modeling in psycholinguistics: linguistic comprehension and production. . See Bod et al. 2003 , pp. 3996
  38. Jurafsky D, Martin JH. 2021.. Speech and Language Processing. Stanford, CA:: Stanford Univ./Boulder, CO: Univ. Colo. https://web.stanford.edu/∼jurafsky/slp3/ . , 3rd ed.. draft
    [Google Scholar]
  39. Kaisse EM. 1985.. Connected Speech: The Interaction of Syntax and Phonology. San Diego, CA:: Academic
    [Google Scholar]
  40. Kaplan A. 2022.. Categorical and gradient ungrammaticality in optional processes. . Language. In press
    [Google Scholar]
  41. Kawahara S. 2020.. A wug-shaped curve in sound symbolism: the case of Japanese Pokémon names. . Phonology 37::383418
    [Google Scholar]
  42. Kawahara S. 2022.. Testing MaxEnt with sound symbolism: a stripy wug-shaped curve in Japanese Pokémon names. . Language. In press
    [Google Scholar]
  43. Kluender KR, Diehl RL, Wright BA. 1988.. Vowel-length differences before voiced and voiceless consonants: an auditory explanation. . J. Phon. 16::15369
    [Google Scholar]
  44. Kroch A. 1989.. Reflexes of grammar in patterns of language change. . Lang. Var. Change 1::199244
    [Google Scholar]
  45. Labov W. 1969.. Contraction, deletion, and inherent variability of the English copula. . Language 45::71562
    [Google Scholar]
  46. Lau JH, Clark A, Lappin S. 2017.. Grammaticality, acceptability, and probability: a probabilistic view of linguistic knowledge. . Cogn. Sci. 41::120241
    [Google Scholar]
  47. Liberman M, Pierrehumbert J. 1984.. Intonational invariance under changes in pitch range and length. . In Language Sound Structure, ed. M Aronoff, RT Oehrle , pp. 157223. Cambridge, MA:: MIT Press
    [Google Scholar]
  48. Linzen T, Jaeger TF. 2016.. Uncertainty and expectation in sentence processing: evidence from subcategorization distributions. . Cogn. Sci. 40::13821411
    [Google Scholar]
  49. Massaro DW, Cohen MM. 1983. Phonological context in speech perception. . Percept. Psychophys. 34::33848
    [Google Scholar]
  50. McCarthy J, Prince A. 1995.. Faithfulness and reduplicative identity. . In University of Massachusetts Occasional Papers in Linguistics 18: Papers in Optimality Theory, ed. J Beckman, S Urbanczyk, LW Dickey , pp. 249384. Amherst, MA:: Grad. Linguist. Stud. Assoc.
    [Google Scholar]
  51. McMurray B, Aslin RN, Tanenhaus MK, Spivey MJ, Subik D. 2008.. Gradient sensitivity to within-category variation in words and syllables. . J. Exp. Psychol.: Hum. Percept. Perform. 34::160931
    [Google Scholar]
  52. McMurray B, Tanenhaus MK, Aslin RN, Spivey MJ. 2003.. Probabilistic constraint satisfaction at the lexical/phonetic interface: evidence for gradient effects of within-category VOT on lexical access. . J. Psycholinguist. Res. 32::7797
    [Google Scholar]
  53. McPherson L, Hayes B. 2016.. Relating application frequency to morphological structure: the case of Tommo So vowel harmony. . Phonology 33::12567
    [Google Scholar]
  54. Mendoza-Denton N, Hay J, Jannedy S. 2003.. Probabilistic sociolinguistics: beyond the variable rule. . See Bod et al. 2003 , pp. 97138
  55. Moore-Cantwell C, Pater J. 2016.. Gradient exceptionality in Maximum Entropy Grammar with lexically specific constraints. . Catalan J. Linguist. 15::5366
    [Google Scholar]
  56. Morrison GS. 2007.. Logistic regression modelling for first and second language perception data. . In Segmental and Prosodic Issues in Romance Phonology, ed. MJ Solé, P Prieto, J Mascaró , pp. 21936. Amsterdam:: John Benjamins
    [Google Scholar]
  57. Prince A, Smolensky P. 2004.. Optimality Theory: Constraint Interaction in Generative Grammar. Oxford, UK:: Blackwell
    [Google Scholar]
  58. Rousseau P, Sankoff D. 1978.. Advances in variable rule methodology. . In Linguistic Variation: Models and Methods, ed. D Sankoff , pp. 5769. New York:: Academic
    [Google Scholar]
  59. Ryan K. 2019.. Prosodic Weight: Categories and Continua. Oxford, UK:: Oxford Univ. Press
    [Google Scholar]
  60. Sankoff D, Labov W. 1979.. On the uses of variable rules. . Lang. Soc. 8::189222
    [Google Scholar]
  61. Sankoff GS. 1972.. A quantitative paradigm for studying communicative competence. Paper presented at the Conference on the Ethnography of Speaking , Austin, TX:
    [Google Scholar]
  62. Scholes R. 1965.. Phonotactic Grammaticality. The Hague, Neth:.: Mouton
    [Google Scholar]
  63. Smith BW, Pater J. 2020.. French schwa and gradient cumulativity. . Glossa 5::24
    [Google Scholar]
  64. Smolensky P. 1986.. Information processing in dynamical systems: foundations of Harmony Theory. . In Parallel Distributed Processing, ed. JL McClelland, DE Rumelhart, PDP Research Group , pp. 390431. Cambridge, MA:: MIT Press
    [Google Scholar]
  65. Szmrecsanyi B, Grafmiller J, Bresnan J, Rosenbach A, Tagliamonte S, Todd S. 2017.. Spoken syntax in a comparative perspective: the dative and genitive alternation in varieties of English. . Glossa 2::86
    [Google Scholar]
  66. Tagliamonte SA, Baayen RH. 2012.. Models, forests and trees of York English: was/were variation as a case study for statistical practice. . Lang. Var. Change 34::13578
    [Google Scholar]
  67. Treutwein B, Strasburger H. 1999.. Fitting the psychometric function. . Percept. Psychophys. 61::87106
    [Google Scholar]
  68. Velldal E, Oepen S. 2005.. Maximum entropy models for realization ranking. . In Proceedings of the 10th Machine Translation Summit, ed. J-I Tsujii , pp. 10916. Tokyo, Jpn:.: Asia-Pac. Assoc. Mach. Transl.
    [Google Scholar]
  69. Wilson C. 2006.. Learning phonology with substantive bias: an experimental and computational investigation of velar palatalization. . Cogn. Sci. 30::94582
    [Google Scholar]
  70. Wilson C. 2014.. Tutorial on Maximum Entropy models. Lecture presented at the Annual Meeting on Phonology, Mass. Inst. Technol., Cambridge, MA:, Sept. 19
    [Google Scholar]
  71. Wolfram W, Fasold RW. 1974.. The Study of Social Dialects in American English. Englewood Cliffs, NJ:: Prentice Hall
    [Google Scholar]
  72. Zimmermann R. 2017.. Formal and quantitative approaches to the study of syntactic change: three case studies from the history of English. PhD Diss., Univ. Geneva, Geneva:
    [Google Scholar]
  73. Zuraw K. 2000.. Patterned exceptions in phonology. PhD Diss., Univ. Calif., Los Angeles:
    [Google Scholar]
  74. Zuraw K. 2003.. Probability in language change. . See Bod et al. 2003 , pp. 13976
  75. Zuraw K. 2010.. A model of lexical variation and the grammar with application to Tagalog nasal substitution. . Nat. Lang. Linguist. Theory 28::41772
    [Google Scholar]
  76. Zuraw K, Hayes B. 2017.. Intersecting constraint families: an argument for Harmonic Grammar. . Language 93::497548
    [Google Scholar]
  77. Zymet J. 2018.. Lexical propensities in phonology: corpus and experimental evidence, grammar, and learning. PhD Diss., Univ. Calif., Los Angeles:
    [Google Scholar]
/content/journals/10.1146/annurev-linguistics-031220-013128
Loading
/content/journals/10.1146/annurev-linguistics-031220-013128
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error