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运用非词和机器心理语言学技术对ChatGPT进行研究。

Examining Chat GPT with nonwords and machine psycholinguistic techniques.

作者信息

Vitevitch Michael S

机构信息

Spoken Language Laboratory, Department of Speech-Language-Hearing, Sciences & Disorders, University of Kansas, Lawrence, Kansas, USA.

出版信息

PLoS One. 2025 Jun 6;20(6):e0325612. doi: 10.1371/journal.pone.0325612. eCollection 2025.

Abstract

Strings of letters or sounds that lack meaning (i.e., nonwords) have been used in cognitive psychology and psycholinguistics to provide foundational knowledge of human processing and representation, and insights into language-related performance. The present set of studies used the machine psycholinguistic approach (i.e., using nonword stimuli and tasks similar to those used with humans) to gain insight into the performance of Chat GPT in comparison to human performance. In Study 1, Chat GPT was able to provide correct definitions to many extinct words (i.e., real English words that are no longer used). In Study 2 the nonwords were real words in Spanish, and Chat GPT was prompted to provide a word that sounded similar to the nonword. Responses tended to be Spanish words unless the prompt specified that the similar sounding word should be an English word. In Study 3 Chat GPT provided subjective ratings of wordlikeness (and buyability) that correlated with ratings provided by humans, and with the phonotactic probabilities of the nonwords. In Study 4, Chat GPT was prompted to generate a new English word for a novel concept. The results of these studies highlight certain strengths and weaknesses in human and machine performance. Future work should focus on developing AI that complements or extends rather than duplicates or competes with human abilities. The machine psycholinguistic approach may help to discover additional strengths and weaknesses of human and artificial intelligences.

摘要

由缺乏意义的字母串或声音(即非单词)已被认知心理学和心理语言学用于提供人类加工和表征的基础知识,以及对语言相关表现的洞察。本系列研究采用机器心理语言学方法(即使用与人类使用的类似的非单词刺激和任务)来深入了解Chat GPT与人类表现相比的性能。在研究1中,Chat GPT能够为许多已灭绝的单词(即不再使用的真实英语单词)提供正确定义。在研究2中,非单词是西班牙语中的真实单词,并促使Chat GPT提供一个听起来与该非单词相似的单词。除非提示指定听起来相似的单词应为英语单词,否则回答往往是西班牙语单词。在研究3中,Chat GPT提供了与人类提供的评级以及非单词的音位结构概率相关的单词相似度(和可接受性)主观评级。在研究4中,促使Chat GPT为一个新的概念生成一个新的英语单词。这些研究结果突出了人类和机器性能方面的某些优势和劣势。未来的工作应侧重于开发补充或扩展而非复制或与人类能力竞争的人工智能。机器心理语言学方法可能有助于发现人类和人工智能的其他优势和劣势。

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