Research Method of Human Speech System Evolution Based on Complex Social Computing

• Published in: Journal of language teaching and research 2010-05, Vol.1 (3), p.336
• Main Authors: Yun, Jian, Wang, Chunxia
• Format: Article
• Language: English
• Subjects: Complex systems; Computer science; Computers; Genetic algorithms; Human evolution; Humanities; Language; Linguistics; Methods; Phonetics; Research methodology; Social sciences; Speech
• ISSN: 1798-4769; 2053-0684
• DOI: 10.4304/jltr.1.3.336-338

The main concern of diachronic linguistics is carding Language family tree and reconstructing the language with contrast. Since the 1950s, there have been some more effective new diachronic linguistics research method or technology, such as, vocabulary proliferation theories(Shiyuan W,1969), tone genetic linguistics(Matisoff J,1973), glottochronology(Swadesh M,1952), remote comparison methods and language variations theories (Labov W,1994,2001).Diachronic linguistics has achieved great success in the Indo-European languages. [...]due to the lack of historical literature research on Sino-Tibetan languages, diachronic linguistics research encountered in unprecedented resistance. [...]the authors consider that establishing universal suitable diachronic evolution model to replace pure empirical speculation can make the research of language evolution more uniform, objective and scientific. RESEARCH METHOD IN SPEECH SYSTEM EVOLUTION BASED ON COMPLEX SOCIAL COMPUTING A. Several Basic Work In order to implement the research of speech system evolution based on complex social computing, the following four fundamental works should do: (1) Complexity analysis of social characteristics in speech system evolution. [double dagger]@Complexity analysis of the social characteristics (such as, the political, economic, cultural, religious beliefs, social psychological changes, etc.) in speech system evolution should be carried out. [double dagger]ATreat speech system evolution as a complex system, define the boundary conditions, analyze the direction, speed, and nonlinear relationship in system evolution, and do formal description.[double dagger]Bpeople's activities in speech system should be logically analysised and formally descripted. V. CONCLUSION Human speech is a complex system, so the relationship between micro-level behavior of the individual and macro-state of population level is non-linear, even chaotic in this system.This research model may help us to understand the non-linear relationship between the microscopic behavior and macroscopic state of population level in evolution of speech system.