Phonotactic Complexity and its Trade-offs


We present methods for calculating a measure of phonotactic complexity—bits per phoneme—that permits a straightforward cross-linguistic comparison. When given a word, represented as a sequence of phonemic segments such as symbols in the international phonetic alphabet, and a statistical model trained on a sample of word types from the language, we can approximately measure bits per phoneme using the negative log-probability of that word under the model. This simple measure allows us to compare the entropy across languages, giving insight into how complex a language’s phonotactics are. Using a collection of 1016 basic concept words across 106 languages, we demonstrate a very strong negative correlation of −0.74 between bits per phoneme and the average length of words.

Transactions of the Association for Computational Linguistics