This study investigated the relative role of sub-syllabic components in spoken word recognition of Mandarin Chinese using an eye-tracking experiment with a visual world paradigm. Native Mandarin speakers were presented with four pictures and an auditory stimulus. They were required to click the picture according to the sound stimulus they heard, and their eye movements were tracked during this process. For a target word, nine conditions of competitors were constructed in terms of the amount of their phonological overlap with the (...) target: consonant competitor, rime competitor, tone competitor, consonant plus rime competitor, consonant plus tone competitor, rime plus tone competitor, cohort competitor, cohort plus tone competitor, and baseline competitor. A growth curve analysis was conducted with the fixation to competitors, targets, and distractors, and the results showed that competitors with consonant or rime overlap can be adequately activated, while tone overlap plays a weaker role since additional tonal information can strengthen the competitive effect only when it was added to a candidate that already bears much phonological similarity with the target. Mandarin words are processed in an incremental way in the time course of word recognition since different partially overlapping competitors could be activated immediately; like the pattern found in English, both cohort and rime competitors were activated to compete for lexical activation, but these two competitors were not temporally distinctive and mainly differed in the size of their competitive effects. Generally, the gradation of activation based on the phonological similarity between target and candidates found in this study was in line with the continuous mapping models and may reflect a strategy of native speakers shaped by the informative characteristics of the interaction among different sub-syllabic components. (shrink)

This paper presents the hypothesis that the representational repertoire underpinning our ability to process the lexical items of a natural language can be modeled as a system of mental files. To start, I clarify the basic phenomena that an account of lexical knowledge should be able to elucidate. Then, I propose to evaluate whether the mental files theory can be brought to bear on an account of the representational format of lexical knowledge by modeling mental words as recognitional files.