Department of Psychology, The Hebrew University of Jerusalem, Mount Scopus Campus, 9190501, Jerusalem, Israel.
BCBL, Basque Center of Cognition, Brain and Language, San Sebastian, Spain.
Behav Res Methods. 2024 Dec;56(8):8761-8783. doi: 10.3758/s13428-024-02502-4. Epub 2024 Sep 9.
Lexicon projects (LPs) are large-scale data resources in different languages that present behavioral results from visual word recognition tasks. Analyses using LP data in multiple languages provide evidence regarding cross-linguistic differences as well as similarities in visual word recognition. Here we present the first LP in a Semitic language-the Hebrew Lexicon Project (HeLP). HeLP assembled lexical decision (LD) responses to 10,000 Hebrew words and nonwords, and naming responses to a subset of 5000 Hebrew words. We used the large-scale HeLP data to estimate the impact of general predictors (lexicality, frequency, word length, orthographic neighborhood density), and Hebrew-specific predictors (Semitic structure, presence of clitics, phonological entropy) of visual word recognition performance. Our results revealed the typical effects of lexicality and frequency obtained in many languages, but more complex impact of word length and neighborhood density. Considering Hebrew-specific characteristics, HeLP data revealed better recognition of words with a Semitic structure than words that do not conform to it, and a drop in performance for words comprising clitics. These effects varied, however, across LD and naming tasks. Lastly, a significant inhibitory effect of phonological ambiguity was found in both naming and LD. The implications of these findings for understanding reading in a Semitic language are discussed.
词汇项目 (Lexicon projects, LPs) 是不同语言的大型数据资源,呈现了视觉词汇识别任务的行为结果。使用多种语言的 LP 数据进行分析,为视觉词汇识别中的跨语言差异和相似性提供了证据。在这里,我们呈现了第一个闪米特语的 LP——希伯来语词汇项目 (Hebrew Lexicon Project, HeLP)。HeLP 收集了对 10000 个希伯来语单词和非单词的词汇判断 (lexical decision, LD) 反应,以及对 5000 个希伯来语单词的一部分的命名反应。我们使用大规模的 HeLP 数据来估计视觉词汇识别性能的一般预测因子 (词汇性、频率、词长、正字法邻近密度) 和希伯来语特定预测因子 (闪米特结构、存在词缀、语音熵) 的影响。我们的结果揭示了在许多语言中获得的词汇性和频率的典型影响,但词长和邻近密度的影响更为复杂。考虑到希伯来语的特点,HeLP 数据显示,具有闪米特结构的单词比不符合闪米特结构的单词更容易识别,而包含词缀的单词的性能则下降。然而,这些影响在 LD 和命名任务中有所不同。最后,在命名和 LD 中都发现了语音模糊性的显著抑制效应。讨论了这些发现对理解闪米特语阅读的意义。