Examining the acquisition of phonological word-forms with computational experiments

This is the author's accepted manuscript. The original publication is available at http://las.sagepub.com/content/early/2012/10/21/0023830912460513.full.pdfIt has been hypothesized that known words in the lexicon strengthen newly formed representations of novel words, resulting in words with dense neighborhoods being learned more quickly than words with sparse neighborhoods. Tests of this hypothesis in a connectionist network showed that words with dense neighborhoods were learned better than words with sparse neighborhoods when the network was exposed to the words all at once (Experiment 1), or gradually over time, like human word-learners (Experiment 2). This pattern was also observed despite variation in the availability of processing resources in the networks (Experiment 3). A learning advantage for words with sparse neighborhoods was observed only when the network was initially exposed to words with sparse neighborhoods and exposed to dense neighborhoods later in training (Experiment 4). The benefits of computational experiments for increasing our understanding of language processes and for the treatment of language processing disorders are discussed

Online Learning From Input Versus Offline Memory Evolution in Adult Word Learning: Effects of Neighborhood Density and Phonologically Related Practice

This is the author's accepted manuscript. The original publication is available at http://jslhr.pubs.asha.org/article.aspx?articleid=1851189Purpose. This study investigates adult word learning to determine how neighborhood density and practice across phonologically-related training sets influence on-line learning from input during training versus off-line memory evolution during no-training gaps. Method. Sixty-one adults were randomly assigned to learn low or high density nonwords. Within each density condition, participants were trained on one set of words and then were trained on a second set of words, consisting of phonological neighbors of the first set. Learning was measured in a picture-naming test. Data were analyzed using multilevel modeling and spline regression. Results. Steep learning during input was observed, with new words from dense neighborhoods and new words that were neighbors of recently learned words (i.e., second set words) being learned better than other words. In terms of memory evolution, large and significant forgetting was observed during 1-week gaps in training. Effects of density and practice during memory evolution were opposite of those during input. Specifically, forgetting was greater for high density and second set words than for low density and first set words. Conclusion. High phonological similarity, regardless of source (i.e., known words or recent training), appears to facilitate on-line learning from input but seems to impede off-line memory evolution

The influence of known-word-frequency on the acquisition of new neighbors in adults: Evidence for exemplar representations in word-learning

This is the author's accepted manuscript. The original publication is available at http://www.tandfonline.com/doi/abs/10.1080/23273798.2014.912342Previous studies showed that a new word that is similar to many known words will be learned better than a new word that is similar to few known words (Storkel et al., 2006). In the present study we created novel words that were phonological neighbors to lexical hermits—or known words that do not have any phonological neighbors—that varied in frequency of occurrence. After several exposures, participants learned a higher proportion of novel words that were neighbors of high frequency known-words than nonwords that were neighbors of low frequency known-words. The present results have implications for abstractionist versus exemplar models of the mental lexicon and language processing, as well as for accounts of word frequency in models of language processing

Methods for Minimizing the Confounding Effects of Word Length in the Analysis of Phonotactic Probability and Neighborhood Density

This is the author's accepted manuscript. The original is available at http://jslhr.pubs.asha.org/article.aspx?articleid=1781521&resultClick=3Recent research suggests that phonotactic probability (the likelihood of occurrence of a sound sequence) and neighborhood density (the number of words phonologically similar to a given word) influence spoken language processing and acquisition across the lifespan in both normal and clinical populations. The majority of research in this area has tended to focus on controlled laboratory studies rather than naturalistic data such as spontaneous speech samples or elicited probes. One difficulty in applying current measures of phonotactic probability and neighborhood density to more naturalistic samples is the significant correlation between these variables and word length. This study examines several alternative transformations of phonotactic probability and neighborhood density as a means of reducing or eliminating this correlation with word length. Computational analyses of the words in a large database and reanalysis of archival data supported the use of z scores for the analysis of phonotactic probability as a continuous variable and the use of median transformation scores for the analysis of phonotactic probability as a dichotomous variable. Neighborhood density results were less clear with the conclusion that analysis of neighborhood density as a continuous variable warrants further investigation to differentiate the utility of z scores in comparison to median transformation scores. Furthermore, balanced dichotomous coding of neighborhood density was difficult to achieve, suggesting that analysis of neighborhood density as a dichotomous variable should be approached with caution. Recommendations for future application and analyses are discussed

Keywords in the mental lexicon

Network science draws from a number of fields to examine complex systems using nodes to represent individuals and connections to represent relationships between individuals to form a network. This approach has been used in several areas of Psychology to illustrate the influence that the structure of a network has on processing in that system. In the present study the concept of keyplayers in a network (Borgatti, 2006) was examined in the domain of Psycholinguistics. Keyplayers are nodes in a network that, when removed, result in the network fracturing into several smaller components. A set of such nodes was found in a network of phonological word-forms as was another set of foil words, comparable to the “keywords” on a number of lexical and network characteristics. In three conventional psycholinguistic tasks keywords were responded to more quickly and accurately than the foils. A similar trend was observed in an analysis of the keywords and foils (and another set of foils) in the English Lexicon Project. These results open avenues for further exploration of keywords in various areas of language processing, and demonstrate the utility of the network science approach to psycholinguistics and psychology more generally