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단어 명명 과제에서 나타난 빈도 효과:단어처리 인지모형 분석

Word Frequency Effect in Word Naming Tasks: An Analysis of Cognitive Model of Word Processing

이다정|고성룡|주혜리
한국인지과학회 (The Korean Society for Cognitive Science)|2024.12|인지과학 (Korean Journal of Cognitive Science)|제35권 제4호|pp. 305-330|DOI 10.19066/cogsci.2024.35.4.004

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키워드

인지모형cognitive model확산모형word processingdiffusion model단어 처리단어 명명 과제단일경계 확산모형word naming taskone boundary diffusion model
주제분류인지과학

초록

이 연구는 이중 경로 가설과 단어 빈도가 높을수록 단어 명명 속도가 빨라진다는 이전 연구를 기반으로 하여 단어 명명 과제를 통해 단어 빈도 효과를 관찰하고자 했다. 또한 이 연구에서는 주혜리와 고성룡(2021)이 소개한 단일경계 확산모형을 사용하여 단어 명명 과제에서 얻은 데이터를 분석하여 모델의 특정 파라미터와의 관련성을 확인하고자 했다. 실험 결과에서는 고빈도 단어 조건에서 저빈도 단어 조건보다 단어를 더 빠르게 명명하는 반응 시간이 나타났다. 단어 명명 과제에서 얻은 데이터를 분포 분석하고 단일경계 확산모형에 넣어 실행한 결과, 단어 빈도 차이가 정보표집율 파라미터의 차이로 설명될 수 있었다. 실험 결과를 바탕으로 단일경계 확산모형이 단어 명명 과제의 단어 처리 과정을 정보표집율 파라미터로 설명할 수 있으며, 모형이 이중경계이나 파라미터의 변동성 가정과 관계없이 언어 처리 현상을 설명하고 개인의 언어 처리 능력을 예측할 수 있는 유용한 도구임을 재확인하였다.

Abstract

This study aimed to examine the effect of word frequency on word naming responses based on the dual route hypothesis and prior research indicating that higher word frequency leads to faster word naming reactions. First, the effect of word frequency was observed through a word naming task. Additionally, this study utilized the one boundary diffusion model introduced by Choo and Koh (2021) to analyze the data obtained from the word naming task, with the objective of examining the relationship between the model's specific parameters and the observed effects. Experimental results indicated that responses were faster for high frequency words compared to low frequency words. Analysis of the distribution of data obtained from the word naming task, when fitted to the one boundary diffusion model, revealed that differences in word frequency could be accounted for by variations in the drift rate parameter. The findings reaffirm that the one boundary diffusion model can effectively explain the word processing mechanisms in the word naming task through the drift rate parameter. Furthermore, the model proves to be a valuable tool for describing language processing phenomena and predicting individual differences in language processing abilities, regardless of the assumptions related to two boundary models or parameter variability.

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