Language Evolution and Computation Bibliography

We examine the evolution of major grammatical forms and constructions as linguistic manifestations of human cognitive ability, based on historical data from English. We show that the complex linguistic system has arisen as more and more grammaticalized forms have accumulated. Word order and case go back to the earliest language. Tense, aspect, modality, gender, questions, negations, parataxis can be traced back to Proto-Indo-European, and they may go back further. Most crucial is the rise of embedding recursion and its product, the VO word order in Old English. This brought about the transition from the syntactic organization of the clause interwoven with discourse organization to the more strictly syntactic organization of the clause. With this transition, the periphrastic constructions of progressive, perfect and pluperfect, modal auxiliaries, periphrastic do and definite article arose due to speakers' desire to be more specific than was possible with the older forms. We also show the role of high-frequency words in the evolution of the grammatical forms.

We demonstrate that polysemous links have a profound impact on the organization of the semantic graph, conforming it as a small-world network, based on the data from WordNet and A Thesaurus of Old English. We then show that the words with higher frequency and therefore with higher number of meanings construct the higher level of the hypernymy tree and this architecture is robust through the times. We suggest that our quantitative analysis of structural connection patterns in semantic networks provides insights into the functioning of neural architectures in the human brain. Furthermore, we discuss that vast quantities of variable and random utterances are converted into a small-world of fixed forms with fixed meanings by the cooperation between humans in the emergence of lexicon.

In this study, optimization models using Genetic Algorithms are proposed to study the conguration of vowels and tone systems. Similar to previous explanatory models that have been used to study vowel systems, certain criteria, which are assumed to be the principles governing the structure of sound systems, are used to predict optimal vowels and tone systems. In most of the earlier studies only one criterion has been considered. When two criteria are considered, they are often combined into one scalar function. The GA model proposed for the study of tone systems uses a Pareto-ranking method which is highly applicable for dealing with optimization problems having multiple criteria. For optimization of tone systems, perceptual contrast and markedness complexity are considered simultaneously. Although the consistency between the predicted systems and the observed systems is not as significant as those obtained for vowel systems, further investigation along this line is promising.