Journal article
Language and Speech, vol. 64(3), 2020
Biologist, linguist & cognitive scientist
Department of English
University of Vienna
          APA  
          
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          Baumann, A., Kaźmierski, K., & Matzinger, T. (2020). Scaling Laws for Phonotactic Complexity in Spoken English Language Data. Language and Speech, 64(3). https://doi.org/10.1177/0023830920944445
        
          Chicago/Turabian  
          
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          Baumann, Andreas, Kamil Kaźmierski, and Theresa Matzinger. “Scaling Laws for Phonotactic Complexity in Spoken English Language Data.” Language and Speech 64, no. 3 (2020).
        
          MLA  
          
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          Baumann, Andreas, et al. “Scaling Laws for Phonotactic Complexity in Spoken English Language Data.” Language and Speech, vol. 64, no. 3, 2020, doi:10.1177/0023830920944445.
        
BibTeX Click to copy
@article{andreas2020a,
  title = {Scaling Laws for Phonotactic Complexity in Spoken English Language Data},
  year = {2020},
  issue = {3},
  journal = {Language and Speech},
  volume = {64},
  doi = {10.1177/0023830920944445},
  author = {Baumann, Andreas and Kaźmierski, Kamil and Matzinger, Theresa}
}
Two prominent statistical laws in language and other complex systems are Zipf’s law and Heaps’ law. We investigate the extent to which these two laws apply to the linguistic domain of phonotactics—that is, to sequences of sounds. We analyze phonotactic sequences with different lengths within words and across word boundaries taken from a corpus of spoken English (Buckeye). We demonstrate that the expected relationship between the two scaling laws can only be attested when boundary spanning phonotactic sequences are also taken into account. Furthermore, it is shown that Zipf’s law exhibits both high goodness-of-fit and a high scaling coefficient if sequences of more than two sounds are considered. Our results support the notion that phonotactic cognition employs information about boundary spanning phonotactic sequences.