JALEX: Japanese version of lexical decision database

要旨

Several lexical databases have been developed in both English-speaking countries and other countries, leading to numerous studies using these resources. A prominent example is the English Lexicon Project (ELP; Balota et al., 2007), a large-scale database containing behavioral data on English word processing. The ELP provides data for two main tasks: the lexical decision task (LDT) and the speeded naming task. Among these, the LDT is the most commonly utilized in word-processing research, largely because 1) it is easy to implement, and 2) it can be conducted online with relative ease (Lieber et al., 2014).In the LDT, participants are asked to decide as quickly and accurately as possible whether a visually presented string of letters forms a real word or a non-word. By analyzing the response time from when the string is presented until the participant makes a decision, researchers can evaluate the speed of word access and semantic processing. The LDT has been employed not only to assess word processing efficiency and cognitive load but also to investigate the structure of the mental lexicon and concept representation. For example, researchers have examined the relationship between LDT response times and various word properties, including the frequency effect, where more frequent words are processed faster and reexamined using the LDT data (Brysbaert et al., 2011).Numerous psycholinguistic studies have explored the semantic properties of word recognition using LDT data. Recently, LDT databases have expanded beyond English, with resources available in languages such as Chinese (Tse et al., 2017), French (Ferrand et al., 2017), and Spanish (Aguasvivas et al., 2018), allowing for more efficient research across languages. For example, researchers have tested hypotheses involving grounded cognition and embodied cognition (Barsalou, 2008) in word recognition and explored the relationship between word recognition and sensorimotor information across various languages, e.g., English (Pexman et al., 2019; Sidhu et al., 2014), French (Lalancette et al., 2024), and Spanish (Alonso et al., 2018). They further examined theoretical predictions with large-scale survey data, often using lexical decision task (LDT) reaction times as the dependent variable in regression analyses. While earlier findings have supported these theories by showing consistent trends across languages, recent discussions have highlighted cross-linguistic variability in these effects (Alonso et al., 2018; Lalancette et al., 2024). Such hypothesis testing using a database reduces stimulus bias by incorporating many words (see Dymarska et al., 2023) and enables new discoveries through cross-linguistic comparisons.In Japanese, several databases are available, as will be discussed later. For example, databases exist for attributes such as word imageability (Sakuma et al., 2005) and familiarity (Asahara, 2020), each containing evaluative data for tens of thousands of words. These databases have long been used in various ways, such as serving as control variables in numerous Japanese word recognition studies (e.g., Mizuno and Matsui, 2018; Mochizuki and Ota, 2020, 2024). However, no LDT database currently exists for Japanese, posing a challenge to psycholinguistic research on the Japanese language as a result of limited resources. Of course, lexical decision tasks have been widely used in Japanese word recognition studies (e.g., Kawakami, 2002; Kusunose et al., 2013). However, the number of stimulus words used in these studies is significantly smaller compared to databases such as the ELP (Balota et al., 2007). Furthermore, the data are not always publicly available, which limits their utility as resources. Given the increasing emphasis on cross-linguistic validation—particularly in studies of abstract concepts shaped by language and culture (Dove, 2018)—developing a large-scale Japanese LDT database would not only aid Japanese researchers but also contribute to the broader field

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