Past research has demonstrated cross-linguistic, cross-modal, and task-dependent differences in neighborhood density effects, indicating a need to control for neighborhood variables when developing and interpreting research on language processing. The goals of the present paper are two-fold: (1) to introduce CLEARPOND (Cross-Linguistic Easy-Access Resource for Phonological and Orthographic Neighborhood Densities), a centralized database of phonological and orthographic neighborhood information, both within and between languages, for five commonly-studied languages: Dutch, English, French, German, and Spanish; and (2) to show how CLEARPOND can be used to compare general properties of phonological and orthographic neighborhoods across languages. CLEARPOND allows researchers to input a word or list of words and obtain phonological and orthographic neighbors, neighborhood densities, mean neighborhood frequencies, word lengths by number of phonemes and graphemes, and spoken-word frequencies. Neighbors can be defined by substitution, deletion, and/or addition, and the database can be queried separately along each metric or summed across all three. Neighborhood values can be obtained both within and across languages, and outputs can optionally be restricted to neighbors of higher frequency. To enable researchers to more quickly and easily develop stimuli, CLEARPOND can also be searched by features, generating lists of words that meet precise criteria, such as a specific range of neighborhood sizes, lexical frequencies, and/or word lengths. CLEARPOND is freely-available to researchers and the public as a searchable, online database and for download at http://clearpond.northwestern.edu.
Bilingualism profoundly affects the brain, yielding functional and structural changes in cortical regions dedicated to language processing and executive function [Crinion J, et al. (2006) Science 312:1537–1540; Kim KHS, et al. (1997) Nature 388:171–174]. Comparatively, musical training, another type of sensory enrichment, translates to expertise in cognitive processing and refined biological processing of sound in both cortical and subcortical structures. Therefore, we asked whether bilingualism can also promote experience-dependent plasticity in subcortical auditory processing. We found that adolescent bilinguals, listening to the speech syllable [da], encoded the stimulus more robustly than age-matched monolinguals. Specifically, bilinguals showed enhanced encoding of the fundamental frequency, a feature known to underlie pitch perception and grouping of auditory objects. This enhancement was associated with executive function advantages. Thus, through experience-related tuning of attention, the bilingual auditory system becomes highly efficient in automatically processing sound. This study provides biological evidence for system-wide neural plasticity in auditory experts that facilitates a tight coupling of sensory and cognitive functions.
During speech comprehension, bilinguals co-activate both of their languages, resulting in cross-linguistic interaction at various levels of processing. This interaction has important consequences for both the structure of the language system and the mechanisms by which the system processes spoken language. Using computational modeling, we can examine how cross-linguistic interaction affects language processing in a controlled, simulated environment. Here we present a connectionist model of bilingual language processing, the Bilingual Language Interaction Network for Comprehension of Speech (BLINCS), wherein interconnected levels of processing are created using dynamic, self-organizing maps. BLINCS can account for a variety of psycholinguistic phenomena, including cross-linguistic interaction at and across multiple levels of processing, cognate facilitation effects, and audio-visual integration during speech comprehension. The model also provides a way to separate two languages without requiring a global language-identification system. We conclude that BLINCS serves as a promising new model of bilingual spoken language comprehension.
We examined the influence of bilingual experience and inhibitory control on the ability to learn a novel language. Using a statistical learning paradigm, participants learned words in two novel languages that were based on the International Morse Code. First, participants listened to a continuous stream of words in a Morse code language to test their ability to segment words from continuous speech. Since Morse code does not overlap in form with natural languages, interference from known languages was minimized. Next, participants listened to another Morse code language composed of new words that conflicted with the first Morse code language. Interference in this second language was high due to conflict between languages and due to the presence of two colliding cues (compressed pauses between words and statistical regularities) that competed to define word boundaries. Results suggest that bilingual experience can improve word learning when interference from other languages is low, while inhibitory control ability can improve word learning when interference from other languages is high. We conclude that the ability to extract novel words from continuous speech is a skill that is affected both by linguistic factors, such as bilingual experience, and by cognitive abilities, such as inhibitory control.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.