Cover not available
Article published In:
International Journal of Corpus Linguistics
Vol. 24:4 (2019) ► pp.522–535
Short paper

Phonological CorpusTools

Software for doing phonological analysis on transcribed corpora

| University of British Columbia
| University of British Columbia
| University of British Columbia
Phonological analysis increasingly involves the quantification of various lexical and/or usage statistics, such as phonotactic probabilities, the functional loads of various phonemic contrasts, or neighbourhood densities. This paper presents Phonological CorpusTools, a free, open-source software for conducting such phonological analyses on transcribed corpora. The motivations for creating the software are given, along with an overview of the structure of the program, its analysis algorithms, and its applications within phonology.
Keywords: phonology, frequency, software, functional load, predictability of distribution
Article outline
  • 1.Introduction
  • 2.Types of corpora
  • 3.Corpora, transcriptions, and features
    • 3.1Transcriptions and inventories
    • 3.2Using tiers
  • 4.Analyses and output
  • 5.Applications and access
  • Acknowledgements
  • Notes
  • References
Published online: 1 November 2019
DOI logo
https://doi.org/10.1075/ijcl.18009.hal
References (36)
References
Baayen, R. H., Piepenbrock, R., & Gulikers, L. (1995). The CELEX Lexical Database: English Linguistic Guide. Linguistic Data Consortium, University of Pennsylvania. Retrieved from [URL] (last accessed August 2019).
Bod, R., Hay, J., & Jannedy, S. (Eds.). (2003). Probabilistic Linguistics. Cambridge, MA: MIT Press. DOI logoGoogle Scholar
Boersma, P., & Weenink, D. (2019). Praat: Doing phonetics by computer (Version 6.0.50) [Computer program]. Retrieved from [URL] (last accessed March 2019).
Brent, M. R. (1999). An efficient, probabilistically sound algorithm for segmentation and word discovery. Machine Learning, 34(1–3), 71–105. DOI logoGoogle Scholar
Brysbaert, M., & New, B. (2009). Moving beyond Kučera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English. Behavior Research Methods, 41(4), 977–990. DOI logoGoogle Scholar
Bybee, J. L. (2001). Phonology and Language Use. Cambridge: Cambridge University Press. DOI logoGoogle Scholar
Chomsky, N., & Halle, M. (1968). The Sound Pattern of English. New York, NY: Harper & Row.Google Scholar
Cohen Priva, U. (2008). Using information content to predict phone deletion. In N. Abner & J. Bishop (Eds.), Proceedings of the 27th West Coast Conference on Formal Linguistics (pp. 90–98). Somerville, MA: Cascadilla Proceedings Project.Google Scholar
Durand, J., Gut, U., & Kristoffersen, G. (Eds.). (2014). The Oxford Handbook of Corpus Phonology. Oxford: Oxford University Press. DOI logoGoogle Scholar
Ernestus, M. (2011). Gradience and categoricality in phonological theory. In M. van Oostendorp, C. J. Ewen, E. Hume & K. Rice (Eds.), The Blackwell Companion to Phonology (pp. 2115–2136). Oxford: Wiley-Blackwell. DOI logoGoogle Scholar
Frisch, S. (2011). Frequency effects. In M. van Oostendorp, C. J. Ewen, E. Hume & K. Rice (Eds.), The Blackwell Companion to Phonology (pp. 2137–2163). Oxford: Wiley-Blackwell. DOI logoGoogle Scholar
Goldsmith, J., & Riggle, J. (2012). Information theoretic approaches to phonological structure: The case of Finnish vowel harmony. Natural Language and Linguistic Theory, 30(3), 859–896. DOI logoGoogle Scholar
Greenberg, J. H., & Jenkins, J. (1964). Studies in the psychological correlates of the sound system of American English. Word, 20(1–3), 157–177. DOI logoGoogle Scholar
Hall, K. C. (2009). A Probabilistic Model of Phonological Relationships from Contrast to Allophony (Unpublished doctoral dissertation). The Ohio State University, Columbus, OH.Google Scholar
(2013). A typology of intermediate phonological relationships. The Linguistic Review, 30(2), 215–275. DOI logoGoogle Scholar
(submitted). Corpora and phonological analysis. In B. E. Dresher & H. Van der Hulst (Eds.), The Handbook of the History of Phonology. Oxford: Oxford University Press.
Hall, K. C., Allen, B., Fry, M., Mackie, S., & McAuliffe, M. (2015). Calculating functional load with pronunciation variants. Paper presented at the Workshop on Modeling Variability in Speech, Institute for Natural Language Processing, Stuttgart, Germany.
Hall, K. C., Jaeger, T. F., Hume, E., & Wedel, A. (2018a). The role of predictability in shaping phonological patterns. Linguistics Vanguard, 4(s2), 1–15. DOI logoGoogle Scholar
Hall, K. C., Pine, A., & Schwan, M. D. (2018b). Doing phonological corpus analysis in a fieldwork context. In L. Matthewson, E. A. Guntly & M. Rochemont (Eds.), Wa7 Xweysás i Nqwal’utteníha i Ucwalmícwa: He Loves the People’s Languages: Essays in honour of Henry Davis (pp. 615–630). Vancouver, BC: UBC Occasional Papers in Linguistics.Google Scholar
Hayes, B. (2009). Introductory Phonology. Oxford: Wiley-Blackwell.Google Scholar
Hockett, C. F. (1966). The quantification of functional load: A linguistic problem. U.S. Air Force Memorandum RM-5168-PR.Google Scholar
International Phonetic Association (Ed.) (1999). The Handbook of the International Phonetic Association. Cambridge: Cambridge University Press.Google Scholar
Johnson, K. (2004). Massive reduction in conversational American English. In K. Yoneyama & K. Maekawa (Eds.), Spontaneous Speech: Data and Analysis (pp. 29–54). Tokyo: The International Institute for Japanese Language.Google Scholar
Khorsi, A. (2012). On morphological relatedness. Natural Language Engineering, 19(4), 1–19.Google Scholar
Kullback, S., & Leibler, R. A. (1951). On information and sufficiency. Annals of Mathematical Statistics, 22(1), 79–86. DOI logoGoogle Scholar
Luce, P. A., & Pisoni, D. B. (1998). Recognizing spoken words: The neighborhood activation model. Ear Hear, 19(1), 1–36. DOI logoGoogle Scholar
Pierrehumbert, J. B. (2003). Probabilistic phonology: Discrimination and robustness. In R. Bod, J. Hay & S. Jannedy (Eds.), Probabilistic Linguistics (pp. 177–228). Cambridge, MA: MIT Press.Google Scholar
Pinnow, E., & Connine, C. M. (2014). Phonological variant recognition: Representations and rules. Language and Speech, 57(1), 42–67. DOI logoGoogle Scholar
Pitt, M. A. (2009). The strength and time course of lexical activation of pronunciation variants. Journal of Experimental Psychology: Human Perception and Performance, 35(3), 896–910.Google Scholar
Pitt, M. A., Dilley, L., Johnson, K., Kiesling, S., Raymond, W., Hume, E., & Fosler-Lussier, E. (2007). Buckeye Corpus of Conversational Speech (2nd Release). Retrieved from [URL] (last accessed August 2019).
Rose, Y., MacWhinney, B., Byrne, R., Hedlund, G., Maddocks, K., O’Brien, P., & Wareham, T. (2006). Introducing Phon: A software solution for the study of phonological acquisition. In D. Bamman, T. Magnitskaia & C. Zaller (Eds.), Proceedings of the 30th Annual Boston University Conference on Language Development (pp. 489–500). Somerville, MA: Cascadilla Proceedings Project.Google Scholar
Rose, Y., & MacWhinney, B. (2014). The PhonBank Project: Data and software-assisted methods for the study of phonology and phonological development. In J. Durand, U. Gut & G. Kristoffersen (Eds.), The Oxford Handbook of Corpus Phonology (pp. 308–401). Oxford: Oxford University Press.Google Scholar
Vaden, K. I., Halpin, H. R., & Hickok, G. S. (2009). Irvine Phonotactic Online Dictionary (Version 2.0). Retrieved from [URL] (last accessed August 2019).
Vitevitch, M. S. & Luce, P. A. (2004). A web-based interface to calculate phonotactic probability for words and nonwords in English. Behavior Research Methods, Instruments, and Computers, 36(3), 481–487. DOI logoGoogle Scholar
Wedel, A., Kaplan, A., & Jackson, S. (2013). High functional load inhibits phonological contrast loss: A corpus study. Cognition, 128(2), 179–186. DOI logoGoogle Scholar
Wells, J. C. (n.d.). Computer-coding the IPA: A Proposed Extension of SAMPA. London: University College London. Retrieved from [URL] (last accessed August 2019).
Cited by (8)

Cited by eight other publications

Graves, William W., Hillary J. Levinson, Ryan Staples, Olga Boukrina, David Rothlein & Jeremy Purcell
2024. An inclusive multivariate approach to neural localization of language components. Brain Structure and Function 229:5 ► pp. 1243 ff. DOI logo
Renwick, Margaret E. L.
2024. Robustness and Complexity in Italian Mid Vowel Contrasts. Languages 9:4 ► pp. 150 ff. DOI logo
Tolkacheva, Valeriya, Sonia L E Brownsett, Katie L McMahon & Greig I de Zubicaray
2024. Perceiving and misperceiving speech: lexical and sublexical processing in the superior temporal lobes. Cerebral Cortex 34:3 DOI logo
Alderete, John & Sara Finley
2023. Probabilistic phonology. Language and Linguistics. 語言暨語言學 24:4 ► pp. 565 ff. DOI logo
Graves, William W., Jeremy Purcell, David Rothlein, Donald J. Bolger, Miriam Rosenberg-Lee & Ryan Staples
2023. Correspondence between cognitive and neural representations for phonology, orthography, and semantics in supramarginal compared to angular gyrus. Brain Structure and Function 228:1 ► pp. 255 ff. DOI logo
Sabev, Mitko
2023. Unstressed vowel reduction and contrast neutralisation in western and eastern Bulgarian: A current appraisal. Journal of Phonetics 99 ► pp. 101242 ff. DOI logo
de Vargas, Mauricio Fontana, David Marino, Antoine Weill--Duflos & Jeremy R. Cooperstock
2021. Speaking Haptically: From Phonemes to Phrases With a Mobile Haptic Communication System. IEEE Transactions on Haptics 14:3 ► pp. 479 ff. DOI logo
Munro, Natalie, Elise Baker, Sarah Masso, Lynn Carson, Taiying Lee, Anita M.-Y. Wong & Stephanie F. Stokes
2021. Vocabulary Acquisition and Usage for Late Talkers Treatment: Effect on Expressive Vocabulary and Phonology. Journal of Speech, Language, and Hearing Research 64:7 ► pp. 2682 ff. DOI logo

This list is based on CrossRef data as of 17 october 2024. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.