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Hoppe, Dorothée B.; Rij, Jacolien; Hendriks, Petra; Ramscar, Michael – Cognitive Science, 2020
Linguistic category learning has been shown to be highly sensitive to linear order, and depending on the task, differentially sensitive to the information provided by preceding category markers ("premarkers," e.g., gendered articles) or succeeding category markers ("postmarkers," e.g., gendered suffixes). Given that numerous…
Descriptors: Discrimination Learning, Computational Linguistics, Natural Language Processing, Artificial Languages
Mengliyev, Bakhtiyor; Shahabitdinova, Shohida; Khamroeva, Shahlo; Gulyamova, Shakhnoza; Botirova, Adiba – Journal of Language and Linguistic Studies, 2021
This article is dedicated to the issue of morphological analysis and synthesis of word forms in a linguistic analyzer, which is a significant feature of corpus linguistics. The article discourses in detail the morphological analysis, the creation of artificial language, grammar and analyzer, the general scheme of the analysis program that…
Descriptors: Morphology (Languages), Computational Linguistics, Computer Software, Artificial Languages
Muylle, Merel; Bernolet, Sarah; Hartsuiker, Robert J. – Language Learning, 2020
Several studies found cross-linguistic structural priming with various language combinations. Here, we investigated the role of two important domains of language variation: case marking and word order, for transitive and ditransitive structures. We varied these features in an artificial language learning paradigm, using three different artificial…
Descriptors: Bilingualism, Priming, Language Processing, Language Variation
Dye, Melody – ProQuest LLC, 2017
While information theory is typically considered in the context of modern computing and engineering, its core mathematical principles provide a potentially useful lens through which to consider human language. Like the artificial communication systems such principles were invented to describe, natural languages involve a sender and receiver, a…
Descriptors: Computational Linguistics, Natural Language Processing, Artificial Languages, Computer Software
Johnson, Elizabeth K.; Tyler, Michael D. – Developmental Science, 2010
Past research has demonstrated that infants can rapidly extract syllable distribution information from an artificial language and use this knowledge to infer likely word boundaries in speech. However, artificial languages are extremely simplified with respect to natural language. In this study, we ask whether infants' ability to track transitional…
Descriptors: Cues, Artificial Languages, Testing, Infants
Kapa, Leah Lynn – ProQuest LLC, 2013
Prior research has established an executive function advantage among bilinguals as compared to monolingual peers. These non-linguistic cognitive advantages are largely assumed to result from the experience of managing two linguistic systems. However, the possibility remains that the relationship between bilingualism and executive function is…
Descriptors: Artificial Languages, Executive Function, Adults, Bilingualism
Hudson Kam, Carla L.; Newport, Elissa L. – Cognitive Psychology, 2009
When natural language input contains grammatical forms that are used probabilistically and inconsistently, learners will sometimes reproduce the inconsistencies; but sometimes they will instead regularize the use of these forms, introducing consistency in the language that was not present in the input. In this paper we ask what produces such…
Descriptors: Form Classes (Languages), Artificial Languages, Adult Learning, Linguistic Input