模拟婴儿期学习后的方式
Canaan M Breiss1, Bruce P Hayes2, Megha Sundara2
1Department of Linguistics, University of Southern California.
Cognitive science
|March 13, 2025
概括
婴儿很早就学会了后,大约6个月. 计算模型表明,首先发现单词对于学习这些单词部分至关重要,与直接寻找附加词的模型不同.
科学领域:
- 认知科学 认知科学
- 发展心理学 发展心理学
- 计算语言学 计算语言学
背景情况:
- 婴儿在6个月大时就能很早地表现出对语法形态词的认识,例如英语后 -s.
- 了解早期形态学获取背后的认知机制是发展语言学的关键挑战.
研究的目的:
- 通过计算建模并理解婴儿获得后知识的过程.
- 评估不同分布式学习模型在复制观察到的后获取命令方面的有效性.
主要方法:
- 训练了一组分布式学习模型在儿童指导言语的语料库上.
- 开发了一种表现最佳的模型,将发言细分为单词,以创建一个原词典,然后使用终点频率和解析可靠性启发式识别后.
- 将该模型的性能与试图直接在发言中添加发现的模型进行比较.
主要成果:
- 性能最好的等级模型成功地模仿了随着适当的参数设置获得后的实验顺序.
- 没有优先考虑单词细分的模型无法匹配收购订单,并产生了虚假的附加名候选人.
- 具体来说,没有词发现步骤的模型从高频词中提取了不可思议的伪附加词.
结论:
- 婴儿的附加词学习似乎是一个层次化的过程,事先单词细分是必不可少的.
- 计算建模支持这样一个假设,即词发现在早期语言学习中先于并促进了附加词发现.
- 这些发现强调了结构化,基于文字的计算模型方法的重要性,其目的是复制婴儿语言学习能力.
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