测试因果过度概括的计算模型:儿童判断和生产数据来自英语,希伯来语,印度语,日语和K'iche'的数据
Ben Ambridge1,2, Laura Doherty1, Ramya Maitreyee1
1University of Liverpool, Liverpool, UK.
Open research Europe
|August 30, 2023
概括
语言学习者通过学习模式避免动词论证结构错误,正如一个计算模型所示,该模型成功地预测了儿童在五种语言中的判断和生产.
科学领域:
- 语言学的语言学.
- 发展心理学 发展心理学
- 计算语言学 计算语言学
背景情况:
- 获得动词论证结构是语言获取研究中的一个核心挑战.
- 过度概括错误,如 *小丑笑了这个人,是常见的,但它们的避免还没有完全理解.
- 以前的计算模型已经预测了成年人对因果形式的动词偏好.
研究的目的:
- 测试计算模型解释儿童动词论证结构概括和过度概括错误的能力.
- 评估模型在五种语言的语法判断和产生的生产数据上的表现.
- 确定一个简单的学习模型是否能够解释成人和儿童的语言学习数据.
主要方法:
- 以前用于成人数据的计算模型被应用于儿童的语法判断和生产数据.
- 该模型在4-6岁儿童的数据上进行了测试,包括英语,希伯来语,印度语,日语和K'iche Mayan.
- 通过将其预测与人类数据相关联来评估模型性能 (r=0.5-0.85的相关性).
主要成果:
- 该计算模型成功地模拟了儿童的语法判断和生产数据在所有五种语言.
- 该模型展示了对未见动词的概括,表明了强大的学习.
- 所有语言的孩子都表现出一些过度概括错误,与之前的自然主义观察一致.
结论:
- 一个简单的学习模型可以有效地解释成人和儿童的数据,包括正确的应用和过度概括错误.
- 该模型为语言学习者如何获得动词参数结构限制提供了可信的机制解释.
- 这项研究支持这样一个观点,即计算模型可以提供对语言学习背后的认知过程有价值的见解.
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