Word Recognition in Different Semantic Context
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Date
2019-05
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The Ohio State University
Abstract
Previous research found that people are more accurate recognizing spoken words in auditory scenes when the distracting sounds are nonspeech compared to speech (Toro, Sinnett, & Soto-Faraco, 2005). Working memory is a type of short-term memory; implying the ability to remember information for a brief period of time (Miyake & Shah, 1999). Working memory capacity (WMC) is the measurement of working memory, representing the capacity limit of information processed in working memory (Conway, et al., 2005). Kane and Engle (2000) found that variation in WMC is related to auditory selective attention. People with higher WMC show less disruption in a distractive listening task than those with lower WMC. Building on this work, Daly, Szostak, and Pitt (in preparation) have found that word recognition is more accurate for those with high than low WMC.
The present study brings these two lines of work together to ask whether WMC’s influence on spoken word recognition differs for different distracting environments (speech vs. nonspeech). We tested the participants’ WMC and have them do a distracting listening task where speech and nonspeech distractors are presented along with words to be recognized. For example, a sentence, e.g., The wing had an exquisite set of feathers, would be played along with a background distractor, and an extra noise mask is played at the onset of “w”. The participants were asked to report what they hear the ambiguous word to be.
Past results lead to the prediction that when the distractor is speech, people with higher WMC will perform much better than people with lower WMC, and when the distractor is nonspeech, the performance difference between individuals with different WMC will greatly diminish. Our results weren’t able to support our hypothesis, that no differences in performance in spoken-word recognition for people with different WMC and no differences in performance in different distractor types. The present study contributes to our understanding of the relationship between WMC and spoken word recognition in different noisy environments.
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Keywords
language, recognition, semantic, Working memory