关于话语连接器对人类和语言模型预测的影响
James Britton1, Yan Cong2, Yu-Yin Hsu1
1Department of Chinese and Bilingual Studies, The Hong Kong Polytechnic University, Hong Kong, China.
Frontiers in human neuroscience
|October 15, 2024
概括
话语连接器有助于语言处理中的事件预测. 虽然中国语言模型显示出一些敏感性,但模型和意大利数据都在与连接驱动的预期反转作斗争.
科学领域:
- 心理语言学 心理语言学
- 计算语言学 计算语言学
- 自然语言处理自然语言处理.
背景情况:
- 人类的句子理解依赖于事件知识进行预测.
- 话语连接词明确地标志着句子关系,但隐含的关系也存在.
- 收缩和对比的连接符表明与事件相关的预测发生了逆转.
研究的目的:
- 调查话语连接器在人类语言处理事件预测中的作用.
- 评估在预训练的语言模型中话语连接器的重要性.
- 专注于宽松和对比的连接,以及它们对期望逆转的影响.
主要方法:
- 发展了意大利和普通话中文故事刺激,其可信度,连贯性和连接性存在度各不相同.
- 收集了人类的可信性判断 (利克尔特尺度) 和阅读时间.
- 利用基于变压器的语言模型的计算建模来获得Surprisal分数.
主要成果:
- 中国语言模型 (NLM) 对可信性和连接性敏感,但与期望反转效应作斗争.
- 意大利语言模型显示,可信性或连接词对Surprisal没有显著的影响.
- 人类数据分析显示了处理一致和不一致的句子序列的差异.
结论:
- 话语连接在事件预测中发挥作用,但它们对预期逆转的影响对于计算模型来说是复杂的.
- 目前的语言模型,特别是意大利语,并不能完全捕捉到人类对话语连接和事件可信性的敏感性.
- 需要进一步的研究来改善计算模型对隐性话语关系和预期操纵的理解.
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