Semantic radicals in Japanese two-character word recognition

Effects of Word Semantic Transparency, Context Length, and L1 Background on CSL Learners' Incidental Learning of Word Meanings in Passage-Level Reading

This study investigated the effects of semantic transparency of Chinese disyllabic compound words on Chinese as a second language (CSL) learners' incidental learning of word meanings in sentence-level reading and passage-level reading. The accuracy of the learners' lexical inferencing was compared among various types of words (transparent, semi-transparent, and opaque words), different context lengths (sentence and passage contexts), and learners with different L1 backgrounds (with and without a Chinese character background in their L1s). In the study, ninety CSL adult learners were asked to infer the meanings of target words in the sentence context and the passage context. The results indicated that the effects of semantic transparency and context length on inferencing accuracy were significant, while the effect of L1 background was not. It was also found that there were significant interactions between transparency and context length as well as between transparency and L1 background.

The time-course of lexical activation in Japanese morphographic word recognition: evidence for a character-driven processing model

This lexical decision study with eye tracking of Japanese two-kanji-character words investigated the order in which a whole two-character word and its morphographic constituents are activated in the course of lexical access, the relative contributions of the left and the right characters in lexical decision, the depth to which semantic radicals are processed, and how nonlinguistic factors affect lexical processes. Mixed-effects regression analyses of response times and subgaze durations (i.e., first-pass fixation time spent on each of the two characters) revealed joint contributions of morphographic units at all levels of the linguistic structure with the magnitude and the direction of the lexical effects modulated by readers' locus of attention in a left-to-right preferred processing path. During the early time frame, character effects were larger in magnitude and more robust than radical and whole-word effects, regardless of the font size and the type of nonwords. Extending previous radical-based and character-based models, we propose a task/decision-sensitive character-driven processing model with a level-skipping assumption: Connections from the feature level bypass the lower radical level and link up directly to the higher character level.