概括
不同的语言共享一个共同的神经基础的意义. 这项研究表明,人工智能语言模型和大脑活动揭示了英语,中文和法语发言者的共同概念表征.
科学领域:
- 神经科学是一个神经科学.
- 认知科学 认知科学
- 计算语言学 计算语言学
背景情况:
- 人类语言在声音,文字和语法方面表现出极大的多样性.
- 尽管存在结构上的差异,但语言传达的含义相似.
- 这种跨语言共享的概念意义的神经基础在很大程度上仍未被探索.
研究的目的:
- 调查不同语言是否汇聚在一个共享的神经基板上,以获得概念意义.
- 为了确定人工智能语言模型 (LMs) 是否可以预测与不同语言中意义相关的大脑活动.
主要方法:
- 利用自然主义的功能磁共振成像 (fMRI) 对英语,中文和法语的母语使用者.
- 在不同的语言上训练语言模型 (LMs),以分析它们的表示空间.
- 开发了语音编码模型,以将LM嵌入与神经反应对齐,并测试了跨语言的泛化.
主要成果:
- 在不同的语言中训练的语言模型汇聚到类似的嵌入空间中,特别是在中间层.
- 在一种语言的神经数据上训练的编码模型成功地预测了其他语言的听众的大脑活动.
- 预测模型的泛化发生在高级语言和默认模式的大脑区域.
结论:
- 意思的神经表征是不同语言的说话者共享的.
- 在不同语言中训练的语言模型捕捉了这个共享的语义空间.
- 共享的意义来自于人类的互动和一个共同的世界,超越语言的多样性.
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