Scaling Laws for Phonotactic Complexity in Spoken English Language Data

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.