形式到意义映射以及在新型文字处理中明确形态组合的影响
Rolando Bonandrini1, Simona Amenta1, Simone Sulpizio1
1Department of Psychology, University of Milano-Bicocca, Milan, Italy.
Cognitive psychology
|August 20, 2023
概括
计算模型表明,通过识别形态线索,从字母模式中理解单词的含义得到了增强. 显而易见的形态分析改善了人类词识别模型,特别是附加的伪词.
科学领域:
- 认知科学 认知科学
- 计算语言学 计算语言学
- 心理语言学 心理语言学
背景情况:
- 只有正写线索可以提供语义信息.
- 形态线索可能提供额外的语义优势.
- 对于语义访问模型来说,理解附加的伪词是一个挑战.
研究的目的:
- 通过计算来评估形态线索对正义线索的优势,用于含义诱导.
- 为了比较含义访问模型与或没有明确的形态信息.
- 为了更好地解释人类在识别附加的伪词的表现.
主要方法:
- 对附加的伪词的词汇决策任务数据进行重新分析.
- 开发一个基于n-gram的模型,使用来自单词形式的语义变量.
- 与模型进行比较,将基于组合的语义变量从形态变量中结合起来.
主要成果:
- 从字母模式 (拼写) 中可以提取语义信息.
- 一个包含明确形态信息的计算模型显著改善了对人类数据的适应性.
- 改进的模型更好地解释了附加的伪词的识别.
结论:
- 显而易见的形态分析有助于语义访问超出了拼写处理.
- 计算模型从整合形态信息中受益,以反映人类认知.
- 形态线索对于理解新的,附加的单词形式至关重要.
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