摘 要

随着语言间的联系日益紧密，Ulrich Weinreich提出了干扰理论。随之语言学界不断涌现出各种二语习得理论，如迁移理论、模因论和动态系统理论等。其中动态系统理论在应用语言学研究中的应用，主要分为介绍基本理论以及研究二语习得两大方面，对理论的构建具有重大意义。为了进一步探究运用动态系统理论阐述二语对一语所产生的影响的可行性，本文将通过回归广府粤语的发展历史，基于动态系统理论分析二语（英语）对一语（粤语）产生的逆向效应。

本文将粤语的发展分为了四个动态发展过程：初始状态、非重建平衡态、变异和非线性发展，并在每个动态中分别讨论分析英语对于语音、词汇和句式三个方面的影响。研究发现，在语音方面，由于粤语语音“吸态盘”拥有较强的吸附力，英语对其影响不大；在词汇方面，随着英语对粤语的影响逐渐深化，粤语出现了大量音译词；而在句式方面，英语的进入也促进了粤英混合语码现象的出现。这个动态发展过程揭示了在英语的影响下，粤语会产生不可预测的动态变化，这丰富了动态系统理论，为分析二语对一语产生的逆向效应研究提供借鉴。

关键词：动态系统理论；粤语；英语；逆向效应

Contents

1. Introduction 1

2. Demonstration 1

2.1 Dynamic System Theory 1

2.2 Literature Review 3

2.3 The Impact of English on Cantonese 4

2.3.1 The Initial State 4

2.3.2 The Attractor State 7

2.3.3 The Variation 8

2.3.4 The Non-linearity 11

3. Conclusion 12

3.1 Major Findings 12

3.2 Implications 13

3.3 Limitations and Suggestions for Further Study 13

Works Cited 14

Bibliography 15

The Impact of English on Cantonese Based on Dynamic System Theory

1. Introduction

Since 1990s, more and more researchers of Applied Linguistics have reckoned that the development of a language is a complex dynamic process with nonlinear features. They apply Dynamic Systems Theory (DST), stemming from Classical Mechanics which is a critical branch of natural science, to Applied Linguistics, especially to Second Language Acquisition. After Larsen-Freeman (1977) combined Dynamic System Theory and Second Language Acquisition together, linguists from home and abroad have been inspired to put more emphasis on this new theory. Nowadays, however, the analyses and applications of this theory are still lingering on the phases of introducing the fundamental principles (e.g. de Bot, 2007; Wang, 2017; Zhan, 2018, etc.) and analyzing SLA (e.g. Shen and Lv, 2018, etc.). Besides, linguists seldom use Dynamic System Theory to study the development of dialects. Therefore, in order to provide some physical evidences for the interaction of two languages, this thesis will explore and analyze the impact of English on the development of Cantonese, especially the spoken Cantonese in Guangzhou, from the perspective of Dynamic System Theory, with the focus on pronunciation, lexicon and syntactic structure by generalizing its developing history.

1. Demonstration
   1. Dynamic System Theory

Dynamic System Theory (also called “DST”) is a newly developing linguistic theory following those traditional theories, such as Transfer Theory, Memetics and so on. A dynamic system is the system developing and changing with times. The fundamental feature of a system is to change itself with times, so all systems are changing and developing all the time. Dynamic System Theory, stemming from Classical Mechanics at first, was applied to Applied Linguistics in “Chaos/ Complexity Science and Second Language Acquisition” by Larsen-Freeman (1997) for the first time. Not only did she establish the basic frame of Dynamic System Theory used in SLA, but she also inspired other linguists to focus on this new theory. Throughout the applications of Dynamic System Theory in Applied Linguistics, researchers at home and abroad can be divided into two major groups.

One group of these linguists put more emphasis on introducing what Dynamic System Theory actually is. Dynamic System Theory considers the developing track of a language as four steps, including Initial State, Attractor State, Variation and Non-linearity. (Liu and Li, 2017) Nowadays, there are a large number of studies explaining these four steps in detail. (de Bot, 2007; Shen and Lv, 2008; Xu, 2015; Su, 2018, etc.) It believes that linguistic systems consist of many subsystems whose tiny changes can somehow influence the entire systems to reach at the non-linearity level. And this kind of process is like the well-known Butterfly Effect. Nevertheless, these influences are not as obvious as we expect because this developing process will be hamstrung by some repulsive force, which is known as Fossilization, namely, Attractor State (Su, 2018) in Dynamic System Theory. In other words, the developing process of a language is to transform the target language from Attractor State into Variation and then to cause unpredictable results. In fact, this process is similar to the process that quantitative changes lead to qualitative changes in philosophy. When a language is at Attractor State, it is also at a stable quantitative level. On the contrary, it is at a turbulent qualitative level.