学习一种语言与诱导语法相比
1Department of Philosophy, University of California, Davis, United States of America.
Cognition
|March 20, 2024
概括
标准的语言学习模型无法捕捉人类如何学习语言. 他们忽视了影响语言数据的非语法因素,挑战了从数据到语法的简单反向推断.
科学领域:
- 计算语言学 计算语言学
- 发展心理学 发展心理学
- 认知科学 认知科学
背景情况:
- 目前的语言学习计算模型假设学习者从语言数据中诱导语法规则.
- 这些模型往往忽略了非语法系统对语言数据的影响.
研究的目的:
- 挑战语言学习的标准计算模型.
- 论证人类语言学习从根本上不同于从数据中诱导规则.
- 突出非语法系统在塑造语言输入中的作用.
主要方法:
- 对标准模型的理论论证.
- 支持另一个观点的经验论据.
- 分析语言数据与语法能力之间的关系.
主要成果:
- 标准模型是不够的,因为它们假定数据是语法的直接产物.
- 非语法系统在很大程度上塑造了儿童所遇到的语言数据.
- 从语言数据到语法能力的简单反向推断受到破坏.
结论:
- 人类语言的获取不仅仅是为了诱导语法规则.
- 非语法因素的影响对于理解语言学习至关重要.
- 未来的模型必须考虑语言使用中的系统的复杂相互作用.
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