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简单句法习得计算模型的影响因素分析

Factors Analysis for a Computational Model of Emergent Simple Syntax

中文摘要英文摘要

本文旨在研究儿童语言习得计算模型的外部语言输入和内部参数对系统学习、理解、产生简单句法的影响。以一个模拟儿童语言一词阶段到二词阶段(O2T)的计算模型为切入点,本文采用量化模拟的实验方法,集中考察系统容量(习得知识量)及评测输出(系统根据所学理解和产生简单句法的质量)所受语言输入和模型参数的影响,并提出贡献词、相关词串/概念、临界抽象因子三个影响因素。贡献词包含了语言输入中的句法信息;相关词串/概念包含了其中与新句法相关联的句法信息;临界抽象因子是系统实现创新性学习的关键。实验结果表明贡献词和相关词串/概念对系统容量及评测输出的作用远大于语言输入的其他信息;临界抽象因子与相关词串/概念联合控制评测输出,前者的取值变化可导致外延过宽或内延过窄。类似实验结果已在MOSAIC模型上得到,成功验证了本文提出的影响因素具备一定程度上的一般性。基于两个模型实验结果的相异之处,文章进一步讨论了MOSAIC模型和O2T模型的区别。

his paper proposes several factors for computational models of early child language acquisition, giving a better explanation on how external language input and intrinsic parameter affect learning, comprehension and production of simple syntax. Taking a model simulating transition from one-word stage to two-word stage (O2T) as beginning, the paper gives quantitative simulation based investigations on how the language input and parameter affect the volume of system (i.e. how much is learned) and evaluation output (i.e. how well the learned can be used by the system to comprehend or produce simple syntax). Factors including contributing word, related string/concept and critical abstract factor, have been figured out to uncover underlying reasons. Contributing words bring syntax information from language input to the system; related strings/concepts relate the learned syntax to new syntax; and abstract factor is crucial for the ability of generative learning. Experiment results show that contributing word and related string/concept have much greater influence respectively on the volume of system and evaluation output, compared to other information the language input contains. Jointly with related string/concept, critical abstract factor controls evaluation output. And there exists value ranges of critical abstract factor for the occurrence of under-extension and over-extension. After that, the paper makes similar investigation on MOSAIC (i.e. a mature and widely-accepted computational model of syntax acquisition), and get similar results, which indicate some degree of generality of the factors. In the light of discrepancies between the results, the paper also gets a clearer image of MOSAIC by discussing its differences from O2T model.

余昊、王小捷

语言学

自然语言处理语言习得计算模型贡献词相关词串临界抽象因子

Natural language processinglanguage acquisitioncomputational modelcontributing wordrelated stringcritical abstract factor

余昊,王小捷.简单句法习得计算模型的影响因素分析[EB/OL].(2010-11-15)[2025-08-23].http://www.paper.edu.cn/releasepaper/content/201011-307.点此复制

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