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Title: Self-organization and language evolution : system, population and individual
Other Titles: Zi zu zhi yu yu yan yan hua : xi tong, qun ti he ge ti
自組織与語言演化 : 系統, 群體和個體
Authors: Ke, Jinyun (柯津云)
Department: Dept. of Electronic Engineering
Degree: Doctor of Philosophy
Issue Date: 2004
Publisher: City University of Hong Kong
Subjects: Language acquisition
Language and languages -- Origin
Self-organizing systems
Notes: CityU Call Number: P116.K4 2004
Includes bibliographical references (leaves 253-283)
Thesis (Ph.D.)--City University of Hong Kong, 2004
iii, xv, 310 leaves : ill. ; 30 cm.
Type: Thesis
Abstract: This thesis proposes a framework adopting the self-organization theory for the study of language evolution. Self-organization explains collective behaviors and evolution with the observation that the patterns at the global level in a complex system are often properties spontaneously emergent from the numerous local interactions among the individual components, and they cannot be understood by only examining the individual components. Language can be viewed as such emergent properties instead of products from some innate blueprint in humans. We highlight the importance of recognizing language at two distinctive but inter-dependent levels of existence, i.e. in the idiolect and in the communal language, and a self-organizing process existing at each of the two levels. It is necessary to clarify what phenomena are properties of the idiolects, and what properties are the collective behaviors at the population level. In linguistics, however, very often an abstract language system is taken as the object of analysis. This level of analysis disregards the distinction between idiolect and communal language, and neglects the heterogeneous nature of language at both levels. As a consequence, explanations for observed patterns based on this abstract level of analysis are often inadequate. However, this is a necessary step for linguists to identify interesting phenomena in the first place. At this abstract level of analysis, the self-organization framework can also be applied. It is assumed that the abstract language system self-organizes. A study on homophony in languages is taken as an example to illustrate the analysis at this level. It is shown that the existence of homophony reflects several self-organization characteristics in a dynamic process of language evolution, such as the predictable degree of homophony, the disyllabification in Chinese dialects, the differentiation of homophone pairs in grammatical class. We are further interested in how the self-organization is implemented. To answer this question, we need to look into the idiolects in this self-organizing process, to know how the idiolects are formed and affect each other. Language change provides an informative window in addressing these issues. Language change is the result of the collective behaviors of idiolects, even as it affects the idiolects. The heterogeneity among idiolects is exposed to the greatest extent in on-going changes. An on-going sound change in Cantonese is taken as a case study to scrutinize the heterogeneity in the self-organizing processes. The fieldwork data reveal a large degree of variation both in the population (VT-I) and in the set of words (VT-II). Another type of variation (VT-III) is highlighted, that is, a word may also show variation within one single speaker. But this VT-III within speakers only exists in a proportion, but not all, of the words subject to the change. Also we find that if a speaker has some words consistently in the unchanged state and some words in the changed state, then this speaker must have some other words in the variation state. Most speakers show the existence of VT-III, but they vary in degree. The observed individual differences in the degree of VT-III suggest that the large heterogeneity may be not only accounted for by the variability of linguistic input, but also by individuals’ different learning styles. We hypothesize two types of lexical learning styles, i.e. probabilistic and categorical learning. These differences in learning styles suggest that when we examine the agent’s internal properties in the self-organization framework, it is not only necessary to examine the commonalities among agents, but also the differences among them. In addition to empirical studies, this thesis employs computational modeling as a major tool for investigation, as modeling provides effective ways to test hypotheses beyond empirical studies, and suggests new questions. After a brief review of the modeling studies in the field, some models developed in this thesis for language origin and language change are reported. The first model is to simulate the emergence of a consistent vocabulary from a set of random mappings between meanings and forms. It emphasizes the importance of implementing the actual process of interaction among agents, and the cumulative effect on agents’ linguistic behaviors. The model suggests that the Saussurean sign with identical speaking and listening mappings may not be a biological predisposition from natural selection, but rather a result from the process of language learning and use. The process exhibits a phase transition from a long period of small oscillation to an abrupt convergence. Such phase transition is often observed in self-organizing systems. The second model simulates language change as innovation diffusion, and examines the effects of various factors, including some concerning properties of agents and some affecting agents’ interactions. By comparing the outcome under different conditions, the model illustrates the importance of incorporating realistic assumptions, such as finite population size, age-dependent propensity to change, different learning environment in a social network, etc. The model compares the dynamics of language change in different types of network structures and shows that in non-regular networks, the rate of innovation diffusion increases little as population size increases. The model also tests the effect of the two types of hypothesized learning styles, and shows that in a population with the presence of probabilistic learners, an innovation with a small advantage will easily spread into the population and lead to a change. This may explain why language changes are so frequent. This thesis demonstrates that both empirical and modeling studies on language evolution can greatly benefit from adopting a self-organization framework. The convergence and interplay of the two lines of exploration, i.e. biological bases in agents and the long term effect of interactions among them, should bring us a deeper understanding of how language has evolved and is evolving.
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