Vaibhav Jalan
2009
Language Diversity across the Consonant Inventories: A Study in the Framework of Complex NetworksPDF
EACL 2009 Workshop on Cognitive Aspects of Computational Language Acquisition, 2009
In this paper, we attempt to explain the emergence of the linguistic diversity that exists across the consonant inventories of some of the major language families of the world through a complex network based growth model. There is only a single parameter for this model that is ...MORE ⇓
In this paper, we attempt to explain the emergence of the linguistic diversity that exists across the consonant inventories of some of the major language families of the world through a complex network based growth model. There is only a single parameter for this model that is meant to introduce a small amount of randomness in the otherwise preferential attachment based growth process. The experiments with this model parameter indicates that the choice of consonants among the languages within a family are far more preferential than it is across the families. The implications of this result are twofold -- (a) there is an innate preference of the speakers towards acquiring certain linguistic structures over others and (b) shared ancestry propels the stronger preferential connection between the languages within a family than across them. Furthermore, our observations indicate that this parameter might bear a correlation with the period of existence of the language families under investigation.
2007
Evolution, optimization and language change: the case of Bengali verb inflectionsPDF
Proceedings of Ninth Meeting of the ACL Special Interest Group in Computational Morphology and Phonology, 2007
The verb inflections of Bengali underwent a series of phonological change between 10th and 18th centuries, which gave rise to several modern dialects of the language. In this paper, we offer a functional explanation for this change by quantifying the functional pressures of ease ...MORE ⇓
The verb inflections of Bengali underwent a series of phonological change between 10th and 18th centuries, which gave rise to several modern dialects of the language. In this paper, we offer a functional explanation for this change by quantifying the functional pressures of ease of articulation, perceptual contrast and learnability through objective functions or constraints, or both. The multi-objective and multi-constraint optimization problem has been solved through genetic algorithm, whereby we have observed the emergence of Pareto-optimal dialects in the system that closely resemble some of the real ones.