Simple stochastic processes behind Menzerath's Law
<|reference_start|>Simple stochastic processes behind Menzerath's Law: This paper revisits Menzerath's Law, also known as the Menzerath-Altmann Law, which models a relationship between the length of a linguistic construct and the average length of its constituents. Recent findings indicate that simple stochastic processes can display Menzerathian behaviour, though existing models fail to accurately reflect real-world data. If we adopt the basic principle that a word can change its length in both syllables and phonemes, where the correlation between these variables is not perfect and these changes are of a multiplicative nature, we get bivariate log-normal distribution. The present paper shows, that from this very simple principle, we obtain the classic Altmann model of the Menzerath-Altmann Law. If we model the joint distribution separately and independently from the marginal distributions, we can obtain an even more accurate model by using a Gaussian copula. The models are confronted with empirical data, and alternative approaches are discussed.<|reference_end|>
@article{milička2024simple,
    title={Simple stochastic processes behind Menzerath's Law},
    author={Jiv{r}'i Miliv{c}ka},
    journal={arXiv preprint arXiv:2409.00279},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.00279},
    primaryClass={cs.CL}
}