When task exposure facilitates performance without producing corresponding changes in verbalizable knowledge, learning is said to be implicit. In Experiment 1, event-related potentials (ERPs) were recorded as individuals practiced an implicit structured sequence learning (ISSL) task wherein only some target events required a response. With practice, the ERPs to targets that obeyed the underlyin...

Previous studies have suggested that individuals use both implicit and explicit, as well as rule and exemplar-based knowledge, to make grammaticality judgments in artificial grammar learning (AGL) tasks. Experiment 1 explored the importance of explicit mechanisms in the learning of exemplar and rule-based information by using a dual-task during AGL training. We utilized a balanced chunk strengt...

We have developed a rule learning system that employed Grammar Based Genetic Program ming for knowledge discovery from databases A grammar is used as a template for the rule format Grammar Based Genetic Program ming can guide the evolution and the discovery of meaningful rules The technique Token Competition is used to achieve the learning of multiple rules simultaneously We have applied the ap...

We investigate a new paradigm in the context of learning in the limit, namely, learning correction grammars for classes of computably enumerable (c.e.) languages. Knowing a language may feature a representation of it in terms of two grammars. The second grammar is used to make corrections to the first grammar. Such a pair of grammars can be seen as a single description of (or grammar for) the l...

Language technology has a potential to play a major role in the process of learning a language. Until recently, the use of language technology in systems for language learning has been nearly nonexistent. However, this has not been the case with grammar checkers for second language learners learning English (see e.g. [4, 12, 30, 36]). The question if grammar checkers actually improve second lan...

Artificial grammar learning constitutes a well-established model for the acquisition of grammatical knowledge in a natural setting. Previous neuroimaging studies demonstrated that Broca's area (left BA 44/45) is similarly activated by natural syntactic processing and artificial grammar learning. The current study was conducted to investigate the causal relationship between Broca's area and lear...

In this paper, I describe several approaches to automatic or semiautomatic development of symbolic rules for grammar checkers from the information contained in corpora. The rules obtained this way are an important addition to manually-created rules that seem to dominate in rulebased checkers. However, the manual process of creation of rules is costly, time-consuming and error-prone. It seems th...

This paper introduces a framework for learning structure in natural languages, and reports results from a simple application of it to learning word-syntax of an agglutinative language in an unsupervised manner. Arguably, the learning environment of children acquiring languages provides more information—by means of linguistic interaction and extralinguistic information present in the learning se...

White matter plays an important role in various domains of cognitive function. While disruptions in white matter are known to affect many domains of behavior and cognition, the ability to acquire grammatical regularities has been mostly linked to the left hemisphere, perhaps due to its dependence on linguistic stimuli. The role of white matter in the right hemisphere in grammar acquisition is y...

Constraint Dependency Grammar (CDG) 11, 13] is a constraint-based grammatical formalism that has proven eeective for processing English 5] and improving the accuracy of spoken language understanding systems 4]. However, prospective users of CDG face a steep learning curve when trying to master this powerful formalism. Therefore, a recent trend in CDG research has been to try to ease the burden ...