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一个基于多式联网变压器的工具,用于跨语言自动生成具体性评级

Viktor Kewenig¹, Jeremy I Skipper², Gabriella Vigliocco²

¹Experimental Psychology, University College London, London, UK. ucjuvnk@ucl.ac.uk.

Communications psychology

|July 8, 2025

概括

这项研究引入了一种自动化系统,用于生成可靠的单词和短语的具体性评级,超过人类的准确性. 该工具使用多式联络变压器和情绪微调的语言模型,为研究人员提供更快,更具成本效益的替代方案.

科学领域:

计算语言学计算语言学
心理语言学心理语言学
自然语言处理自然语言处理.

背景情况:

具体性评级对于理解文字处理和语义表示至关重要.
现有的方法依赖于耗时且昂贵的人类评级收集.
跨语言和多词表达 (MWE) 数据给评级系统带来了独特的挑战.

研究的目的:

开发一种自动化,可靠和可扩展的方法来生成具体性评级.
在不同语言和表达式类型中实现超越人类水平的可靠性.
为研究人员提供一个可访问的工具来评估单词的具体性.

主要方法:

使用多式联接变压器与情感调整的语言模型相结合.
将视觉和情感信息融入到语境感知语言嵌入中.
实现了自动语言检测和翻译,用于跨语言通用化.

主要成果:

与人类评分取得了很高的相关性:单个英语单词的0.93和多个单词表达式的0.85.
证明了成功的跨语言概括到一个未见的爱沙尼亚语库 (N=35,979).
自动化系统有效地捕捉了从具体到抽象概念的频谱.

结论:

开发的自动化系统为传统的人类评级提供了情境敏感和可靠的替代方案.
这种方法大大减少了与收集具体性数据相关的时间和成本.
可访问的基于Web的接口 (具体性.eu) 可用于研究使用.

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