Dataset Information

Differences in Working Memory Capacity Affect Online Spoken Word Recognition: Evidence From Eye Movements.

ABSTRACT: Individual differences in working memory capacity have been gaining recognition as playing an important role in speech comprehension, especially in noisy environments. Using the visual world eye-tracking paradigm, a recent study by Hadar and coworkers found that online spoken word recognition was slowed when listeners were required to retain in memory a list of four spoken digits (high load) compared with only one (low load). In the current study, we recognized that the influence of a digit preload might be greater for individuals who have a more limited memory span. We compared participants with higher and lower memory spans on the time course for spoken word recognition by testing eye-fixations on a named object, relative to fixations on an object whose name shared phonology with the named object. Results show that when a low load was imposed, differences in memory span had no effect on the time course of preferential fixations. However, with a high load, listeners with lower span were delayed by ∼550 ms in discriminating target from sound-sharing competitors, relative to higher span listeners. This follows an assumption that the interference effect of a memory preload is not a fixed value, but rather, its effect is greater for individuals with a smaller memory span. Interestingly, span differences affected the timeline for spoken word recognition in noise, but not offline accuracy. This highlights the significance of using eye-tracking as a measure for online speech processing. Results further emphasize the importance of considering differences in cognitive capacity, even when testing normal hearing young adults.

SUBMITTER: Nitsan G

PROVIDER: S-EPMC6480998 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:This study investigated the relative role of sub-syllabic components (initial consonant, rime, and tone) in spoken word recognition of Mandarin Chinese using an eye-tracking experiment with a visual world paradigm. Native Mandarin speakers (all born and grew up in Beijing) 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 (e.g., tang2 "candy"), nine conditions of competitors were constructed in terms of the amount of their phonological overlap with the target: consonant competitor (e.g., ti1 "ladder"), rime competitor (e.g., lang4 "wave"), tone competitor (e.g., niu2 "cow"), consonant plus rime competitor (e.g., tang1"soup"), consonant plus tone competitor (e.g., tou2 "head"), rime plus tone competitor (e.g., yang2 "sheep"), cohort competitor (e.g., ta3 "tower"), cohort plus tone competitor (e.g., tao2 "peach"), and baseline competitor (e.g., xue3 "snow"). A growth curve analysis was conducted with the fixation to competitors, targets, and distractors, and the results showed that (1) 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. (2) Mandarin words are processed in an incremental way in the time course of word recognition since different partially overlapping competitors could be activated immediately; (3) 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.

Dataset Information

Differences in Working Memory Capacity Affect Online Spoken Word Recognition: Evidence From Eye Movements.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets