Volume 22, Issue 2
  • ISSN 1568-1475
  • E-ISSN: 1569-9773
Buy:$35.00 + Taxes


One striking commonality between languages is their Zipfian distributions: A power-law distribution of word frequency. This distribution is found across languages, speech genres, and within different parts of speech. The recurrence of such distributions is thought to reflect cognitive and/or communicative pressures and to facilitate language learning. However, research on Zipfian distributions has mostly been limited to spoken languages. In this study, we ask whether Zipfian distributions are also found across signed languages, as expected if they reflect a universal property of human language. We find that sign frequencies and ranks in three sign language corpora (BSL, DGS and NGT) show a Zipfian relationship, similar to that found in spoken languages. These findings highlight the commonalities between spoken and signed languages, add to our understanding of the use of signs, and show the prevalence of Zipfian distributions across language modalities, supporting the idea that they facilitate language learning and communication.


Article metrics loading...

Loading full text...

Full text loading...


  1. Bank, R., Crasborn, O., & van Hout, R.
    (2016) The prominence of spoken language elements in a sign language. Linguistics, 54(6), 1281–1305. 10.1515/ling‑2016‑0030
    https://doi.org/10.1515/ling-2016-0030 [Google Scholar]
  2. Bentz, C., Alikaniotis, D., Samardžić, T., & Buttery, P.
    (2017) Variation in word frequency distributions: Definitions, measures and implications for a corpus-based language typology. Journal of Quantitative Linguistics, 24(2–3), 128–162. 10.1080/09296174.2016.1265792
    https://doi.org/10.1080/09296174.2016.1265792 [Google Scholar]
  3. Bickerton, D.
    (1983) Creole languages. Scientific American, 249(1), 116–123. 10.1038/scientificamerican0783‑116
    https://doi.org/10.1038/scientificamerican0783-116 [Google Scholar]
  4. Blasi, D. E., Michaelis, S. M., & Haspelmath, M.
    (2017) Grammars are robustly transmitted even during the emergence of creole languages. Nature Human Behaviour, 1(10), 723–729. 10.1038/s41562‑017‑0192‑4
    https://doi.org/10.1038/s41562-017-0192-4 [Google Scholar]
  5. Borstell, C.
    (2022) Searching and utilizing corpora [Review of Searching and utilizing corpora]. InJ. Fenlon & J. A. Hochgesang (Eds.), Signed Language Corpora, pp.115–118. Gallaudet University Press. 10.2307/j.ctv2rcnfhc.9
    https://doi.org/10.2307/j.ctv2rcnfhc.9 [Google Scholar]
  6. Brennan, M.
    (1982) An introduction to the visual world of BSL. InD. Brien (Ed.), Dictionary of British Sign Language/English, pp.1–133. Faber & Faber.
    [Google Scholar]
  7. Brentari, D.
    (1998) A prosodic model of sign language phonology. MIT Press.
    [Google Scholar]
  8. (2006) Effects of language modality on word segmentation: An experimental study of phonological factors in a sign language. InS. Anderson, L. Goldstein, & C. Best (Eds.). Papers in laboratory phonology (Vol.81), pp.155–164. De Gruyter Mouton. 10.1515/9783110197211.1.155
    https://doi.org/10.1515/9783110197211.1.155 [Google Scholar]
  9. Brentari, D., & Goldin-Meadow, S.
    (2017) Language emergence. Annual review of linguistics, 31, 363–388. 10.1146/annurev‑linguistics‑011415‑040743
    https://doi.org/10.1146/annurev-linguistics-011415-040743 [Google Scholar]
  10. Brentari, D., & Padden, C. A.
    (2001) Native and foreign vocabulary in American Sign Language: A lexicon with multiple origins. InD. Brentari (Ed.), Foreign vocabulary in sign languages: A cross-linguistic investigation of word formation, pp.87–119. Lawrence Erlbaum. 10.4324/9781410601513‑10
    https://doi.org/10.4324/9781410601513-10 [Google Scholar]
  11. Caselli, N. K., & Pyers, J. E.
    (2017) The road to language learning is not entirely iconic: Iconicity, neighborhood density, and frequency facilitate acquisition of sign language. Psychological Science, 28(7), 979–987. 10.1177/0956797617700498
    https://doi.org/10.1177/0956797617700498 [Google Scholar]
  12. Caselli, N., Sevcikova Sehyr, Z., Cohen-Goldberg, A. M., & Emmorey, K.
    (2017) ASL-LEX: A lexical database of American Sign Language. Behavior Research Methods, 49(2), 784–801. 10.3758/s13428‑016‑0742‑0
    https://doi.org/10.3758/s13428-016-0742-0 [Google Scholar]
  13. Chater, N., & Brown, G. D.
    (1999) Scale-invariance as a unifying psychological principle. Cognition, 69(3), B17–B24. 10.1016/S0010‑0277(98)00066‑3
    https://doi.org/10.1016/S0010-0277(98)00066-3 [Google Scholar]
  14. Christiansen, M. H., & Chater, N.
    (2008) Language as shaped by the brain. The Behavioral and Brain Sciences, 31(5), 489–508; discussion509–558. 10.1017/S0140525X08004998
    https://doi.org/10.1017/S0140525X08004998 [Google Scholar]
  15. Clauset, A., Shalizi, C. R., & Newman, M. E. J.
    (2009) Power-law distributions in empirical data. SIAM Review, 51(4), 661–703. 10.1137/070710111
    https://doi.org/10.1137/070710111 [Google Scholar]
  16. Clerkin, E. M., Hart, E., Rehg, J. M., Yu, C., & Smith, L. B.
    (2017) Real-world visual statistics and infants’ first-learned object names. Philosophical Transactions of the Royal Society B: Biological Sciences, 372 (1711), 1–8. 10.1098/rstb.2016.0055
    https://doi.org/10.1098/rstb.2016.0055 [Google Scholar]
  17. Cooperrider, K., Abner, N., & Goldin-Meadow, S.
    (2018) The palm-up puzzle: Meanings and origins of a widespread form in gesture and sign. Frontiers in Communication, 31, 1–14. 10.3389/fcomm.2018.00023
    https://doi.org/10.3389/fcomm.2018.00023 [Google Scholar]
  18. Cormier, K., Fenlon, J., Gulamani, S., & Smith, S.
    (2017) BSL corpus annotation conventions. Annotation Convention, Vol.31, 2–15.
    [Google Scholar]
  19. Cormier, K., Quinto-Pozos, D., Sevcikova, Z., & Schembri, A.
    (2012) Lexicalisation and de-lexicalisation processes in sign languages: Comparing depicting constructions and viewpoint gestures. Language & Communication, 32(4), 329–348. 10.1016/j.langcom.2012.09.004
    https://doi.org/10.1016/j.langcom.2012.09.004 [Google Scholar]
  20. Coupé, C., Oh, Y., Dediu, D., & Pellegrino, F.
    (2019) Different languages, similar encoding efficiency: Comparable information rates across the human communicative niche. Science Advances, 5(9), eaaw2594. 10.1126/sciadv.aaw2594
    https://doi.org/10.1126/sciadv.aaw2594 [Google Scholar]
  21. Crasborn, O. & Zwitserlood, I.
    (2008) The Corpus NGT: An online corpus for professionals and laymen, InO. Crasborn, T. Hanke, E. Efthimiou, I. Zwitserlood & E. Thoutenhoofd (eds.), Construction and exploitation of Sign Language corpora. 3rd Workshop on the Representation and Processing of Sign Languages, pp.44–49. ELDA.
    [Google Scholar]
  22. Crasborn, O., Bank, R., Zwitserlood, I., Van Der Kooij, E., De Meijer, A., Sáfár, A., & Ormel, E.
    (2015) Annotation conventions for the Corpus NGT, version 3. Centre for Language Studies & Department of Linguistics, Radboud University Nijmegen.
    [Google Scholar]
  23. Crasborn, O., Sloetjes, H.
    (2008) Enhanced ELAN functionality for sign language corpora. In: 6th International Conference on Language Resources and Evaluation (LREC 2008)/3rd Workshop on the Representation and Processing of Sign Languages: Construction and Exploitation of Sign Language Corpora, pp.39–43.
    [Google Scholar]
  24. Crasborn, O., Zwitserlood, I. & Ros, J.
    (2008) The Corpus NGT. An open access digital corpus of movies with annotations of Sign Language of the Netherlands. Centre for Language Studies, Radboud University Nijmegen. Available athttps://archive.mpi.nl/tla/islandora/object/tla:1839_00_0000_0000_0004_DF8E_6?asOfDateTime=2018-03-02T11:00:00.000Z (last access12 March 2024). ISLRN: https://www.islrn.org/resources/175-346-174-413-3/ (last access13 March 2024).
    [Google Scholar]
  25. De Vos, C.
    (2012) Sign-spatiality in Kata Kolok: How a village sign language in Bali inscribes its signing space [Doctoral dissertation, Radboud University Nijmegen].
  26. Diessel, H.
    (2007) Frequency effects in language acquisition, language use, and diachronic change. New Ideas in Psychology, 25(2), 108–127. 10.1016/j.newideapsych.2007.02.002
    https://doi.org/10.1016/j.newideapsych.2007.02.002 [Google Scholar]
  27. Ellis, N. C.
    (2002) Frequency effects in language processing: A review with implications for theories of implicit and explicit language acquisition. Studies in second language acquisition, 24(2), 143–188. 10.1017/S0272263102002024
    https://doi.org/10.1017/S0272263102002024 [Google Scholar]
  28. Emmorey, K.
    (2001) Language, cognition, and the brain: Insights from sign language research. Psychology Press. 10.4324/9781410603982
    https://doi.org/10.4324/9781410603982 [Google Scholar]
  29. Erting, C. J., Prezioso, C., & O’Grady Hynes, M.
    (1990) The interactional context of deaf mother-infant communication. InFrom gesture to language in hearing and deaf children, pp.97–106. Springer Verlag. 10.1007/978‑3‑642‑74859‑2_9
    https://doi.org/10.1007/978-3-642-74859-2_9 [Google Scholar]
  30. Fenlon, J., Cormier, K., & Schembri, A.
    (2015a) Building BSL SignBank: The lemma dilemma revisited. International Journal of Lexicography, 28(2), 169–206. 10.1093/ijl/ecv008
    https://doi.org/10.1093/ijl/ecv008 [Google Scholar]
  31. Fenlon, J., Schembri, A., Johnston, T., & Cormier, K.
    (2015b) Documentary and corpus approaches to sign language research. Research methods in sign language studies: A practical guide, pp.156–172. Wiley-Blackwell. 10.1002/9781118346013.ch10
    https://doi.org/10.1002/9781118346013.ch10 [Google Scholar]
  32. Fenlon, J., Schembri, A., Rentelis, R., Vinson, D., & Cormier, K.
    (2014a) Using conversational data to determine lexical frequency in British Sign Language: The influence of text type. Lingua, 1431, 187–202. 10.1016/j.lingua.2014.02.003
    https://doi.org/10.1016/j.lingua.2014.02.003 [Google Scholar]
  33. Fenlon, Jordan, Kearsy Cormier, Ramas Rentelis, Adam Schembri, Katherine Rowley, Robert Adam, & Bencie Woll
    (2014b) BSL SignBank: A lexical database of British Sign Language (1st edn). London: Deafness, Cognition and Language Research Centre, University College London.
    [Google Scholar]
  34. Ferrer-i-Cancho, R. & Solé, R. V.
    (2003) Least effort and the origins of scaling in human language. Proceedings of the National Academy of Sciences, 100(3), 788–791. 10.1073/pnas.0335980100
    https://doi.org/10.1073/pnas.0335980100 [Google Scholar]
  35. Ferrer-i-Cancho, R.
    (2016) Compression and the origins of Zipf’s law for word frequencies. Complexity, 21(S2), 409–411. 10.1002/cplx.21820
    https://doi.org/10.1002/cplx.21820 [Google Scholar]
  36. Gibson, E., Futrell, R., Piantadosi, S. T., Dautriche, I., Bergen, L., & Levy, R.
    (2019) How efficiency shapes human language. Trends in Cognitive Sciences, 23(5), 389–407. 10.1016/j.tics.2019.02.003
    https://doi.org/10.1016/j.tics.2019.02.003 [Google Scholar]
  37. Goldberg, A. E., Casenhiser, D. M., & Sethuraman, N.
    (2004) Learning argument structure generalizations. Cognitive Linguistics, 15(3), 289–316. 10.1515/cogl.2004.011
    https://doi.org/10.1515/cogl.2004.011 [Google Scholar]
  38. Hendrickson, A. T., & Perfors, A.
    (2019) Cross-situational learning in a Zipfian environment, Cognition1891, 11–22. 10.1016/j.cognition.2019.03.005
    https://doi.org/10.1016/j.cognition.2019.03.005 [Google Scholar]
  39. Holzrichter, A. S., & Meier, R. P.
    (2000) Child-directed signing in American sign language. InC. Chamberlain, J. P. Morford, & R. I. Mayberry (Eds.), Language acquisition by eye, pp.25–40. Lawrence Erlbaum.
    [Google Scholar]
  40. Johnston, T.
    (2012) Lexical frequency in sign languages. Journal Of Deaf Studies And Deaf Education, 17(2), 163–193. 10.1093/deafed/enr036
    https://doi.org/10.1093/deafed/enr036 [Google Scholar]
  41. Johnston, T., & De Beuzeville, L.
    (2016) Auslan corpus annotation guidelines. Auslan Corpus.
    [Google Scholar]
  42. Johnston, T., & Schembri, A.
    (2007) Australian Sign Language (Auslan): An introduction to sign language linguistics. Cambridge University Press. 10.1017/CBO9780511607479
    https://doi.org/10.1017/CBO9780511607479 [Google Scholar]
  43. Johnston, T.
    (2010) From archive to corpus: transcription and annotation in the creation of signed language corpora. International Journal of Corpus Linguistics, 151, 10–131. 10.1075/ijcl.15.1.05joh
    https://doi.org/10.1075/ijcl.15.1.05joh [Google Scholar]
  44. Klima, E. S., & Bellugi, U.
    (1979) The Signs of Language. Harvard University Press.
    [Google Scholar]
  45. Konrad, R., Hanke, T., Langer, G., Blanck, D., Bleicken, J., Hofmann, I., Jeziorski, O., König, L., König, S., Nishio, R., Regen, A., Salden, U., Wagner, S., Worseck, S., Böse, O., Jahn, E., Schulder, M.
    (2020a) MEINE DGS – annotiert. Öffentliches Korpus der Deutschen Gebärdensprache, 3. Release / MY DGS – annotated. Public Corpus of German Sign Language, 3rd release [Dataset]. Hamburg University.
    [Google Scholar]
  46. Konrad, R., Hanke, T., Langer, G., König, S., König, L., Nishio, R., and Regen, A.
    (2020b) Öffentliches DGS-Korpus: Annotationskonventionen / Public DGS Corpus: Annotation conventions. Project Note AP03-2018-01, DGS-Korpus project, IDGS, Hamburg University.
    [Google Scholar]
  47. Kurumada, C., Meylan, S. C., & Frank, M. C.
    (2013) Zipfian frequency distributions facilitate word segmentation in context. Cognition, 127(3), 439–453. 10.1016/j.cognition.2013.02.002
    https://doi.org/10.1016/j.cognition.2013.02.002 [Google Scholar]
  48. Langer, G., Müller, A., & Wähl, S.
    (2018) Queries and Views in iLex to Support Corpus-based Lexicographic Work on German Sign Language (DGS). InM. Bono, E. Efthimiou, S. E. Fotinea, T. Hanke, J. Hochgesang, J. Kristoffersen, J. Mesch & Y. Osugi (eds.) Involving the Language Community. Proceedings of the 8th Workshop on the Representation and Processing of Sign Language. 11th International Conference on Language Resources and Evaluation (LREC 2018), Miyazaki, Japan, pp.107–114. ELRA.
    [Google Scholar]
  49. Lavi-Rotbain, O., & Arnon, I.
    (2019) Children learn words better in low entropy. Proceedings of the 41thth Annual Conference of the Cognitive Science Society, pp.631–637. Cognitive Science Society.
    [Google Scholar]
  50. (2020) The learnability consequences of Zipfian distributions: Word segmentation is facilitated in more predictable distributions. PsyArXiv. [preprint MS, pp.1–17] 10.31234/osf.io/xwgpk
    https://doi.org/10.31234/osf.io/xwgpk [Google Scholar]
  51. (2021) Visual statistical learning is facilitated in Zipfian distributions. Cognition, 2061, 1044921, 1–8. 10.1016/j.cognition.2020.104492
    https://doi.org/10.1016/j.cognition.2020.104492 [Google Scholar]
  52. (2022) The learnability consequences of Zipfian distributions in language. Cognition, 2231, 1050381, 1–14. 10.1016/j.cognition.2022.105038
    https://doi.org/10.1016/j.cognition.2022.105038 [Google Scholar]
  53. (2023) Zipfian distributions in child-directed speech. Open Mind, 71, 1–30. 10.1162/opmi_a_00070
    https://doi.org/10.1162/opmi_a_00070 [Google Scholar]
  54. Liddell, S. K.
    (2003) Grammar, gesture and meaning in American Sign Language. Cambridge University Press, Cambridge. 10.1017/CBO9780511615054
    https://doi.org/10.1017/CBO9780511615054 [Google Scholar]
  55. Lillo-Martin, D. C., & Gajewski, J.
    (2014) One grammar or two? Sign Languages and the nature of human language. Wiley Interdisciplinary Reviews: Cognitive Science, 5(4), 387–401. 10.1002/wcs.1297
    https://doi.org/10.1002/wcs.1297 [Google Scholar]
  56. Lillo-Martin, D., & Klima, E. S.
    (1990) Pointing out differences: ASL pronouns in syntactic theory. Theoretical Issues in Sign Language Research, 11, 191–210
    [Google Scholar]
  57. Linders, G. M., & Louwerse, M. M.
    (2020) Zipf’s law in human-machine dialog. Proceedings of the 20th ACM International Conference on Intelligent Virtual Agents, pp.1–8. Association for Computing Machinery. 10.1145/3383652.3423878
    https://doi.org/10.1145/3383652.3423878 [Google Scholar]
  58. Mandelbrot, B.
    (1953) An informational theory of the statistical structure of language. Communication Theory, 21, 486–502.
    [Google Scholar]
  59. Manin, D.
    (2008) Zipf’s law and avoidance of excessive synonymy. Cognitive Science, 32(7), 1075–1098. 10.1080/03640210802020003
    https://doi.org/10.1080/03640210802020003 [Google Scholar]
  60. Masataka, N., Morford, J., & Mayberry, R.
    (2000) The role of modality and input in the earliest stage of language acquisition: Studies of Japanese Sign Language. InChamberlain, C., Morford, J. P., & Mayberry, R. (Eds.), Language acquisition by eye, pp.3–24. Lawrence Erlbaum.
    [Google Scholar]
  61. McDonald, B. H.
    (1985) Productive and frozen lexicon in ASL: An old problem revisited. InW. Stokoe & V. Volterra (Eds.), SLR ’83: Proceedings of the 3rd International Symposium on Sign Language Research, pp.254–259. CNR & Linstok Press.
    [Google Scholar]
  62. McKee, D., & Kennedy, G. D.
    (2006) The distribution of signs in New Zealand Sign Language. Sign Language Studies, 6(4), 372–390. 10.1353/sls.2006.0027
    https://doi.org/10.1353/sls.2006.0027 [Google Scholar]
  63. Mehri, A., & Jamaati, M.
    (2017) Variation of Zipf’s exponent in one hundred live languages: A study of the Holy Bible translations. Physics Letters, Section A: General, Atomic and Solid State Physics, 381(31), 2470–2477. 10.1016/j.physleta.2017.05.061
    https://doi.org/10.1016/j.physleta.2017.05.061 [Google Scholar]
  64. Meier, R.
    (1990) Person deixis in ASL. InS. Fischer & P. Siple (Eds.), Theoretical issues in sign language research, Vol.11, pp.175–190. University of Chicago Press.
    [Google Scholar]
  65. Meir, I., & Sandler, W.
    (2007) A language in space: the story of israeli sign language. Psychology Press. 10.4324/9780203810118
    https://doi.org/10.4324/9780203810118 [Google Scholar]
  66. Meir, I., Sandler, W., Padden, C., & Aronoff, M.
    (2010) Emerging sign languages. InM. Marschark & P. Spencer (Eds.), Oxford handbook of deaf studies, language, and education, Vol.21, pp.267–280. Oxford University Press. 10.1093/oxfordhb/9780195390032.013.0018
    https://doi.org/10.1093/oxfordhb/9780195390032.013.0018 [Google Scholar]
  67. Morford, J. P., & MacFarlane, J.
    (2003) Frequency Characteristics of American Sign Language. Sign Language Studies, 3(2), 213–225. 10.1353/sls.2003.0003
    https://doi.org/10.1353/sls.2003.0003 [Google Scholar]
  68. Newman, M. E. J.
    (2005) Power laws, Pareto distributions and Zipf’s law. Contemporary Physics, 46(5), 323–351. 10.1080/00107510500052444
    https://doi.org/10.1080/00107510500052444 [Google Scholar]
  69. Novogrodsky, R., & Meir, N.
    (2020) Age, frequency, and iconicity in early sign language acquisition: Evidence from the Israeli Sign Language MacArthur–Bates Communicative Developmental Inventory. Applied Psycholinguistics, 41(4), 817–845. 10.1017/S0142716420000247
    https://doi.org/10.1017/S0142716420000247 [Google Scholar]
  70. Orfanidou, E., Adam, R., Morgan, G., & McQueen, J. M.
    (2010) Recognition of signed and spoken language: Different sensory inputs, the same segmentation procedure. Journal of Memory and Language, 62(3), 272–283. 10.1016/j.jml.2009.12.001
    https://doi.org/10.1016/j.jml.2009.12.001 [Google Scholar]
  71. Orfanidou, E., McQueen, J. M., Adam, R., & Morgan, G.
    (2015) Segmentation of British Sign Language (BSL): Mind the gap!Quarterly Journal of Experimental Psychology, 68(4), 641–663. 10.1080/17470218.2014.945467
    https://doi.org/10.1080/17470218.2014.945467 [Google Scholar]
  72. Perlman, M., Little, H., Thompson, B., & Thompson, R. L.
    (2018) Iconicity in signed and spoken vocabulary: a comparison between American Sign Language, British Sign Language, English, and Spanish. Frontiers in psychology, 9, 1433, pp.2–14. 10.3389/fpsyg.2018.01433
    https://doi.org/10.3389/fpsyg.2018.01433 [Google Scholar]
  73. Piantadosi, S. T.
    (2014) Zipf’s word frequency law in natural language: A critical review and future directions. Psychonomic Bulletin & Review, 21(5), 1112–1130. 10.3758/s13423‑014‑0585‑6
    https://doi.org/10.3758/s13423-014-0585-6 [Google Scholar]
  74. Sandler, W., & Lillo-Martin, D.
    (2001) Natural sign languages. InM. Aronoff and J. Rees-Miller (Eds.), Handbook of linguistics, pp.533–562. Blackwell.
    [Google Scholar]
  75. (2006) Sign Language and linguistic universals. Cambridge University Press. 10.1017/CBO9781139163910
    https://doi.org/10.1017/CBO9781139163910 [Google Scholar]
  76. Sandler, Wendy
    (2016) What comes first in language emergence?InN. Enfield (Ed.) Dependency in language: On the causal ontology of language systems (Studies in Diversity in Linguistics 99), pp.67–86. Language Science Press.
    [Google Scholar]
  77. Schembri, Adam, Jordan Fenlon, Ramas Rentelis, & Kearsy Cormier
    (2017) British Sign Language Corpus Project: A corpus of digital video data and annotations of British Sign Language 2008–2017 (3rd edn). University College London. Available athttps://www.bslcorpusproject.org (last access12 March 2024).
    [Google Scholar]
  78. Schick, B. S.
    (1987) The acquisition of classifier predicates in American Sign Language. [Doctoral Dissertation, Purdue University Indiana].
  79. Schuler, K. D., Reeder, P. A., Newport, E. L., & Aslin, R. N.
    (2017) The Effect of Zipfian Frequency Variations on Category Formation in Adult Artificial Language Learning. Language Learning and Development, 13(4), 357–374. 10.1080/15475441.2016.1263571
    https://doi.org/10.1080/15475441.2016.1263571 [Google Scholar]
  80. Sehyr, Z. S., Caselli, N., Cohen-Goldberg, A. M., & Emmorey, K.
    (2021) The ASL-LEX 2.0 Project: A database of lexical and phonological properties for 2,723 Signs in American Sign Language. The Journal of Deaf Studies and Deaf Education, 26(2), 263–277. 10.1093/deafed/enaa038
    https://doi.org/10.1093/deafed/enaa038 [Google Scholar]
  81. Semple, S., Ferrer-i-Cancho, R., & Gustison, M. L.
    (2022) Linguistic laws in biology. Trends in Ecology and Evolution, 37(1), 53–66. 10.1016/j.tree.2021.08.012
    https://doi.org/10.1016/j.tree.2021.08.012 [Google Scholar]
  82. Senghas, A., & Coppola, M.
    (2001) Children creating language: How Nicaraguan Sign Language acquired a spatial grammar. Psychological science, 12(4), 323–328. 10.1111/1467‑9280.00359
    https://doi.org/10.1111/1467-9280.00359 [Google Scholar]
  83. Shufaniya, A., & Arnon, I.
    (2022) A cognitive bias for Zipfian distributions? Uniform distributions become more skewed via cultural transmission. Journal of Language Evolution, 7(1), 59–80. 10.1093/jole/lzac005
    https://doi.org/10.1093/jole/lzac005 [Google Scholar]
  84. Siegel, J.
    (2008) The emergence of pidgin and creole languages. Oxford University Press. 10.1093/oso/9780199216666.001.0001
    https://doi.org/10.1093/oso/9780199216666.001.0001 [Google Scholar]
  85. Smith, R. G., & Hofmann, M.
    (2020) Lexical frequency analysis of Irish Sign Language. TEANGA, the Journal of the Irish Association for Applied Linguistics, 111, 18–47. 10.35903/teanga.v11i1.162
    https://doi.org/10.35903/teanga.v11i1.162 [Google Scholar]
  86. Stamp, R., Ohanin, O. & Lanesman, S.
    (2022) The Corpus of Israeli Sign Language. Conference Proceedings (LREC): Language Resources (LRs) and Evaluation for Human Language Technologies (HLT), pp.192–197. ELRA.
    [Google Scholar]
  87. Sümer, B., Grabitz, C., & Küntay, A.
    (2017) Early produced signs are iconic: Evidence from Turkish Sign Language. InThe 39th Annual Conference of the Cognitive Science Society (CogSci 2017), pp.3273–3278. Cognitive Science Society.
    [Google Scholar]
  88. Supalla, T.
    (1982) Structure and acquisition of verbs of motion and location in American Sign Language. [Ph.D. dissertation, University of California at San Diego].
  89. Talmy, L.
    (2001, June). Spatial structuring in spoken and signed language. Annual Meeting of the Berkeley Linguistics Society, 27(1), pp.271–300. 10.3765/bls.v27i1.3417
    https://doi.org/10.3765/bls.v27i1.3417 [Google Scholar]
  90. Woltz, D. J., Gardner, M. K., Kircher, J. C., & Burrow-Sanchez, J. J.
    (2012) Relationship between perceived and actual frequency represented by common rating scale labels. Psychological Assessment, 24(4), 995–1007. 10.1037/a0028693
    https://doi.org/10.1037/a0028693 [Google Scholar]
  91. Zipf, G. K.
    (1949) Human behavior and the principle of least effort. Human behavior and the principle of least effort. Addison-Wesley Press.
    [Google Scholar]
  92. Zwitserlood, I.
    (2012) Chapter 8 Classifiers. InR. Pfau, M. Steinbach, & B. Woll (Eds.), Sign Language: An international handbook, pp.158–181. De Gruyter Mouton. 10.1515/9783110261325.158
    https://doi.org/10.1515/9783110261325.158 [Google Scholar]

Data & Media loading...

  • Article Type: Research Article
Keyword(s): sign language; universal properties of language; Zipfian distributions
This is a required field
Please enter a valid email address
Approval was successful
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error