Artificial Grammar Learning Paradigm Research Articles

Are Human Learners Capable of Learning Arbitrary Language Structures

The artificial grammar learning paradigm is a classic method of investigating the influence of universal constraints on shaping learning biases on language acquisition. While this method has been used extensively by linguists to test theoretical claims in generative grammar, one of the most prevalent frameworks in language acquisition, several studies have questioned whether artificial grammar learning reflects language acquisition enough to allow us to use it to draw inferences about the validity of universal constraints, particularly those arising from phonetic naturalness. The current study tests whether artificial grammar learning shows the effect of one robust phonetic naturalness constraint: the restriction on nasal harmony patterns arising from the sonority hierarchy. Nasal harmony is of particular interest because it is one of the few types of harmony that occurs between consonants and vowels, which is an under-researched topic. The results, contrary to the skeptical concerns, showed that participants (n = 120) could learn an artificial grammar involving a natural pattern, but could not learn one corresponding to an arbitrary/phonetically unmotivated pattern in the same way or to the same degree. This study contributes epistemic support to the large body of work using artificial grammar experiments to test phonological operations.

Are People Able to Disentangle Perceptual and Conceptual Fluency? Evidence from Artificial Grammar Learning Experiment

The heuristic of information processing fluency plays an important role in making judgments. Some sources of processing fluency can be relevant or irrelevant to the content of a judgment. In this study, we aim to check whether individuals can distinguish different sources of fluency or fluency has a general effect on judgments. We used an artificial grammar learning paradigm (AGL) and tested the effects of different fluency sources (grammaticality and perceptual noise) on the judgment of grammaticality or of subjective ease of reading. It was found that both grammaticality and perceptual noise affected grammaticality judgements: the grammatical and the less noisy strings were evaluated more often as grammatical. However, only the perceptual noise affected judgments of subjective ease of reading. The results obtained provide evidence that fluency may contribute to the effects of implicit learning. It is possible that the processing fluency heuristic is the additional factor of judgement in the lack of explicit knowledge. Perhaps, perceptual noise provided almost complete explicit information for judgment of ease of reading; hence there was no need for additional heuristics. Another possible explanation is that perceptual fluency sources affect the early stages of information processing in a mandatory manner, unlike the conceptual ones. Overall, results are better explained by the non-specificity fluency hypothesis supporting the impossibility to distinguish between different fluency sources.

On the learnability of level-based and unit-based tonal OCP generalizations: An artificial grammar learning study

In previous research of tonal phonology, contour tones were assumed to be phonologically presented not only as a sequence of level tones but also as a single unit. Obligatory Contour Principle (OCP) constraints, by extension, were thought to prohibit identical level tones associated to adjacent terminal nodes (OCP-Terminal) and identical adjacent tonal units (OCP-Unit). This proposal has nevertheless been challenged theoretically and empirically. This study seeks to offer new experimental evidence to help solve the debate by comparing the learnability of the two OCP generalizations in an artificial grammar learning paradigm. In Exp I, we exposed disyllabic tonal patterns conforming either to OCP-Terminal or to OCP-Unit to two target groups of learners, who were then tested if they could extend the hidden generalization to their auditory acceptability judgment of novel disyllabic items. Exp II had the same exposure phase but required learners to produce novel disyllabic items with tonal combinations of their choice. In both experiments, the two target groups demonstrated signs of learning target OCP generalizations from different channels. Crucially, learners implicitly acquired the OCP-Terminal generalization but only learned the OCP-Unit pattern as explicit knowledge. These findings led us to conclude that OCP-Unit may not be involved in implicit and automatized phonological computation.

Literacy effects on artificial grammar learning (AGL) with letters and colors: evidence from preschool and primary school children

abstractLiteracy affects many aspects of language and cognition, including the shift from a more holistic mode of processing to a more analytical part-based mode of processing. Here we examined whether this shift impacts the ability of preschool and primary school children to learn the rules underlying a finite-state grammar using an artificial grammar learning (AGL) paradigm implemented with either linguistic (letters) or non-linguistic (colors) materials to further examine if children’s AGL performance was modulated by type of stimuli. Both tasks involved a training phase in which half of the preschool children and half of the primary school children were exposed to a set of either letter or color strings without any information about the rules underlying the construction of those strings. Later, in the test phase, they were asked to decide whether a new set of letter or color strings conformed to those rules to test grammar learning. Results showed that only primary school children showed evidence of learning, and, importantly, only with colors. These findings seem to support the view that learning to read promotes reliance on smaller linguistic units that might hinder the ability of first-graders to learn the rules underlying finite-state grammars implemented with linguistic materials.

통계적 학습과 언어: 영어 관계절과 수일치 구문 중심으로

This study investigates whether sensitivity to nonadjacent and adjacent dependency rules in an artificial grammar learning paradigm (i.e., statistical learning ability) predicts L2 learners’ performance in comprehending two different types of English structures. A total of 110 L1-Korean participants completed the four tasks: two artificial grammar learning tasks, involving nonadjacent and adjacent dependency rules, and two self-paced English reading tasks, involving English relative clauses and adjacent number agreement in noun phrases. The results show that their statistical learning scores predicted the L2 learners’ performance only in processing object relative clauses: the ability to discover the nonadjacent pattern in artificial grammar learning is correlated with comprehension accuracy on object relative clauses, but not on adjacent number agreement. The findings of this study indicate that the statistical learning ability to discover a particular pattern (a nonadjacent dependency) can be considered a predictor in comprehending long-distance dependency patterns in the L2. These also illuminate the role of implicit learning processes of language learning, which will have pedagogical implications for second language instruction as well.

Mini Pinyin: A modified miniature language for studying language learning and incremental sentence processing.

Artificial grammar learning (AGL) paradigms are used extensively to characterise (neuro)cognitive bases of language learning. However, despite their effectiveness in characterising the capacity to learn complex structured sequences, AGL paradigms lack ecological validity and typically do not account for cross-linguistic differences in sentence comprehension. Here, we describe a new modified miniature language paradigm - Mini Pinyin - that mimics natural language as it is based on an existing language (Mandarin Chinese) and includes both structure and meaning. Mini Pinyin contains a number of cross-linguistic elements, including varying word orders and classifier-noun rules. To evaluate the effectiveness of Mini Pinyin, 76 (mean age = 24.9; 26 female) monolingual native English speakers completed a learning phase followed by a sentence acceptability judgement task. Generalised mixed effects modelling revealed that participants attained a moderate degree of accuracy on the judgement task, with performance scores ranging from 25% to 100% accuracy depending on the word order of the sentence. Further, sentences compatible with the canonical English word order were learned more efficiently than non-canonical word orders. We controlled for inter-individual differences in statistical learning ability, which accounted for ~20% of the variance in performance on the sentence judgement task. We provide stimuli and statistical analysis scripts as open-source resources and discuss how future research can utilise this paradigm to study the neurobiological basis of language learning. Mini Pinyin affords a convenient tool for improving the future of language learning research by building on the parameters of traditional AGL or existing miniature language paradigms.

The Neuroscience of Implicit Learning

AbstractOver the past decades, research employing artificial grammar, sequence learning, and statistical learning paradigms has flourished, not least because these methods appear to offer a window, albeit with a restricted view, on implicit learning processes underlying natural language learning. But these paradigms usually provide relatively little exposure, use meaningless stimuli, and do not even necessarily target natural language structures. So the question arises whether they engage the same brain regions as natural language. The aim of this review is to use data from brain imaging, brain stimulation, and the effects of brain damage to identify the main brain regions that show sensitivity to structural regularities in implicit learning paradigms and to consider their relationship to natural language processing and learning.

Surface features can deeply affect artificial grammar learning.

Three experiments explored the extent to which surface features explain discrimination between grammatical and non-grammatical strings in artificial grammar learning (AGL). Experiment 1 replicated Knowlton and Squire's (1996) paradigm using either letter strings as in the original study, or an analogous set of color strings to further explore if learning was affected by type of stimuli. Learning arose only with letter strings, but the results were mostly due to the discrimination of non-grammatical strings containing highly salient illegal features. Experiments 2 and 3 tested a new grammar devised to control for those features. Experiment 2 showed reduced grammar learning effects, and again only for letter materials. Experiment 3 explored the effect of additional practice with letter stimuli, and found increased learning only in the spaced practice condition, though additional practice also produced more explicit knowledge. These findings call for further research on the boundary conditions of learning in AGL paradigms.

Is It Possible to Read Other People’s Confidence While Testing Their Implicit Learning?

Recent studies have shown that observers can accurately read a partner’s confidence in their decision without verbal information exchange. The main question of the present study concerns the possibility of an accurate reading of the metacognitive experiences of others if they make decisions based on implicit knowledge. The second question addressed the predictors of such mindreadings if they are possible. The experiment was conducted using an artificial grammar learning paradigm. Participants worked in dyads: the Learner implicitly learned to classify stimuli as grammatical and non-grammatical, and the Observer observed the classification process while having no access to the stimuli, and not communicating with the partner. The Observer’s judgment of the Learner’s confidence, as well as the Learner's judgment of his/her confidence, were recorded. The results demonstrate that the Learner's confidence judgments correlate with the Observer's judgments of his/her confidence. Moreover, only the confidence judgments of the Learner correlate with the classification accuracy. It is concluded that intrapersonal confidence judgments and interpersonal confidence judgments are partially guided by the same criteria (in particular, response time), however, the Learners’ judgments of their own confidence in the decisions are more sensitive to the implicit knowledge

Implicit Statistical Learning Across Modalities and Its Relationship With Reading in Childhood.

Implicit statistical learning (ISL) describes our ability to tacitly pick up regularities from our environment therefore, shaping our behavior. A broad understanding of ISL incorporates a great range of possible computations, which render it highly relevant to reading. In the light of this hypothesized relationship, ISL performance was explored in young (M = 8.47 years) typical readers (N = 31) across three different modalities (i.e., visual, auditory, and tactile) using the Artificial Grammar Learning (AGL) paradigm. Adopting repeated measures and correlational designs, the obtained data revealed modality constraints: (1) above-chance performance was observed on the visual and tactile tasks but not on the auditory task, (2) there was no significant correlation of ISL performance across modalities, and (3) split-half reliability of visual and auditory tasks was reasonably high, yet for the tactile task it was close to zero. Evaluating the relation between ISL ability and language skills, we observed a positive correlation between visual ISL performance and phonological awareness. We discuss these findings in view of current perspectives on the nature of ISL and its potential involvement in mastering successful (i.e., accurate and fluent) reading.

Structured Sequence Learning: Animal Abilities, Cognitive Operations, and Language Evolution.

Human language is a salient example of a neurocognitive system that is specialized to process complex dependencies between sensory events distributed in time, yet how this system evolved and specialized remains unclear. Artificial Grammar Learning (AGL) studies have generated a wealth of insights into how human adults and infants process different types of sequencing dependencies of varying complexity. The AGL paradigm has also been adopted to examine the sequence processing abilities of nonhuman animals. We critically evaluate this growing literature in species ranging from mammals (primates and rats) to birds (pigeons, songbirds, and parrots) considering also cross‐species comparisons. The findings are contrasted with seminal studies in human infants that motivated the work in nonhuman animals. This synopsis identifies advances in knowledge and where uncertainty remains regarding the various strategies that nonhuman animals can adopt for processing sequencing dependencies. The paucity of evidence in the few species studied to date and the need for follow‐up experiments indicate that we do not yet understand the limits of animal sequence processing capacities and thereby the evolutionary pattern. This vibrant, yet still budding, field of research carries substantial promise for advancing knowledge on animal abilities, cognitive substrates, and language evolution.

The Role of Anti-harmony in Learning Neutral Vowels

The present study used an artificial grammar learning paradigm to explore the prediction that exposure to anti-harmony might help learners infer that a neutral vowel in a vowel harmony language is transparent. Participants were exposed to a back/round harmony language with a neutral vowel [a]. This neutral vowel either always selected a back vowel suffix, always selected a front vowel suffix, or selected both front-and back vowel suffixes, in adherence to anti-harmony. Results indicated that exposure to a back/round harmony with the neutral vowel selecting either back vowel suffixes, or both front and back vowel suffixes, could induce a bias towards transparent vowels. Assuming that participants inferred that the centralized [a] paired with [o] harmonically, then the predictions that exposure to anti-harmony could induce a bias towards a transparent vowel interpretation were borne out. However, the bias towards a transparent vowel was not significantly different between the anti-harmony conditions and the harmony condition, suggesting that this effect should be replicated with other neutral vowels.

Behavioral and Imaging Studies of Infant Artificial Grammar Learning.

Artificial grammar learning (AGL) paradigms have proven to be productive and useful to investigate how young infants break into the grammar of their native language(s). The question of when infants first show the ability to learn abstract grammatical rules has been central to theoretical debates about the innate vs. learned nature of grammar. The presence of this ability early in development, that is, before considerable experience with language, has been argued to provide evidence for a biologically endowed ability to acquire language. Artificial grammar learning tasks also allow infant populations to be readily compared with adults and non-human animals. Artificial grammar learning paradigms with infants have been used to investigate a number of linguistic phenomena and learning tasks, from word segmentation to phonotactics and morphosyntax. In this review, we focus on AGL studies testing infants' ability to learn grammatical/structural properties of language. Specifically, we discuss the results of AGL studies focusing on repetition-based regularities, the categorization of functors, adjacent and non-adjacent dependencies, and word order. We discuss the implications of the results for a general theory of language acquisition, and we outline some of the open questions and challenges.

An empirical review of language learning based on the micro-artificial grammar-learning paradigm

Since the American psychologist Reber designed and used the micro-miniature artificial grammar-learning paradigm for the first time in 1967, it has already had a history of half a century. This paper mainly discusses micro-artificial grammar development of four types (classic micro-artificial grammar learning of finite state grammar; micro-artificial grammar learning of finite state grammar without semantics; micro-artificial grammar learning of non-finite state grammar with adjustable semantics; and micro-artificial grammar learning of “mini” natural language) and their further significance in the field of language learning.

Non-adjacent Dependency Learning in Humans and Other Animals.

Learning and processing natural language requires the ability to track syntactic relationships between words and phrases in a sentence, which are often separated by intervening material. These nonadjacent dependencies can be studied using artificial grammar learning paradigms and structured sequence processing tasks. These approaches have been used to demonstrate that human adults, infants and some nonhuman animals are able to detect and learn dependencies between nonadjacent elements within a sequence. However, learning nonadjacent dependencies appears to be more cognitively demanding than detecting dependencies between adjacent elements, and only occurs in certain circumstances. In this review, we discuss different types of nonadjacent dependencies in language and in artificial grammar learning experiments, and how these differences might impact learning. We summarize different types of perceptual cues that facilitate learning, by highlighting the relationship between dependent elements bringing them closer together either physically, attentionally, or perceptually. Finally, we review artificial grammar learning experiments in human adults, infants, and nonhuman animals, and discuss how similarities and differences observed across these groups can provide insights into how language is learned across development and how these language‐related abilities might have evolved.

Individual and Developmental Differences in Distributional Learning.

This study examined whether children and adults with developmental language disorder (DLD) could use distributional information in an artificial language to learn about grammatical category membership similarly to their typically developing (TD) peers and whether developmental differences existed within and between DLD and TD groups. Sixteen children ages 7-9 with DLD, 26 age-matched TD children, 17 college students with DLD, and 17 TD college students participated in this task. We used an artificial grammar learning paradigm in which participants had to use knowledge of category membership to determine the acceptability of test items that they had not heard during a training phase. Individuals with DLD performed similarly to TD peers in distinguishing grammatical from ungrammatical combinations, with no differences between age groups. The order in which items were heard at test differentially affected child versus adult participants and showed a relation with attention and phonological working memory as well. Differences in ratings between grammatical and ungrammatical items in this task suggest that individuals with DLD can form grammatical categories from novel input and more broadly use distributional information. Differences in order effects suggest a developmental timeline for sensitivity to updating distributional information.

Artificial Grammar Learning Capabilities in an Abstract Visual Task Match Requirements for Linguistic Syntax.

Whether pattern-parsing mechanisms are specific to language or apply across multiple cognitive domains remains unresolved. Formal language theory provides a mathematical framework for classifying pattern-generating rule sets (or “grammars”) according to complexity. This framework applies to patterns at any level of complexity, stretching from simple sequences, to highly complex tree-like or net-like structures, to any Turing-computable set of strings. Here, we explored human pattern-processing capabilities in the visual domain by generating abstract visual sequences made up of abstract tiles differing in form and color. We constructed different sets of sequences, using artificial “grammars” (rule sets) at three key complexity levels. Because human linguistic syntax is classed as “mildly context-sensitive,” we specifically included a visual grammar at this complexity level. Acquisition of these three grammars was tested in an artificial grammar-learning paradigm: after exposure to a set of well-formed strings, participants were asked to discriminate novel grammatical patterns from non-grammatical patterns. Participants successfully acquired all three grammars after only minutes of exposure, correctly generalizing to novel stimuli and to novel stimulus lengths. A Bayesian analysis excluded multiple alternative hypotheses and shows that the success in rule acquisition applies both at the group level and for most participants analyzed individually. These experimental results demonstrate rapid pattern learning for abstract visual patterns, extending to the mildly context-sensitive level characterizing language. We suggest that a formal equivalence of processing at the mildly context sensitive level in the visual and linguistic domains implies that cognitive mechanisms with the computational power to process linguistic syntax are not specific to the domain of language, but extend to abstract visual patterns with no meaning.

The Nature of Affect in the Structural Mere Exposure Effect

This paper investigates the characteristics of the affective component in the structural mere exposure effect (SMEE). Two approaches are considered – fluency attribution approach (FA) and affect as predictive efficiency approach (APE) – within a predictive coding framework. Using the artificial grammar learning and affective priming paradigms, we demonstrate that a violation of implicitly learned regularities elicits an automatic negative affective response. This result suggests that SMEE can be observed without any overtly evaluative judgment. Participants’ decisions on the grammaticality of stimuli did not change this pattern. We conclude that SMEE is based on the affective response to prediction errors made by the cognitive system and may include the fluency attribution process in the later stages of processing.

Artificial grammar learning in vascular and progressive non-fluent aphasias

Patients with non-fluent aphasias display impairments of expressive and receptive grammar. This has been attributed to deficits in processing configurational and hierarchical sequencing relationships. This hypothesis had not been formally tested. It was also controversial whether impairments are specific to language, or reflect domain general deficits in processing structured auditory sequences.Here we used an artificial grammar learning paradigm to compare the abilities of controls to participants with agrammatic aphasia of two different aetiologies: stroke and frontotemporal dementia.Ten patients with non-fluent variant primary progressive aphasia (nfvPPA), 12 with non-fluent aphasia due to stroke, and 11 controls implicitly learned a novel mixed-complexity artificial grammar designed to assess processing of increasingly complex sequencing relationships. We compared response profiles for otherwise identical sequences of speech tokens (nonsense words) and tone sweeps.In all three groups the ability to detect grammatical violations varied with sequence complexity, with performance improving over time and being better for adjacent than non-adjacent relationships. Patients performed less well than controls overall, and this was related more strongly to aphasia severity than to aetiology. All groups improved with practice and performed well at a control task of detecting oddball nonwords. Crucially, group differences did not interact with sequence complexity, demonstrating that aphasic patients were not disproportionately impaired on complex structures. Hierarchical cluster analysis revealed that response patterns were very similar across all three groups, but very different between the nonsense word and tone tasks, despite identical artificial grammar structures.Overall, we demonstrate that agrammatic aphasics of two different aetiologies are not disproportionately impaired on complex sequencing relationships, and that the learning of phonological and non-linguistic sequences occurs independently. The similarity of profiles of discriminatory abilities and rule learning across groups suggests that insights from previous studies of implicit sequence learning in vascular aphasia are likely to prove applicable in nfvPPA.

Auditory and Visual Sequence Learning in Humans and Monkeys using an Artificial Grammar Learning Paradigm

Language flexibly supports the human ability to communicate using different sensory modalities, such as writing and reading in the visual modality and speaking and listening in the auditory domain. Although it has been argued that nonhuman primate communication abilities are inherently multisensory, direct behavioural comparisons between human and nonhuman primates are scant. Artificial grammar learning (AGL) tasks and statistical learning experiments can be used to emulate ordering relationships between words in a sentence. However, previous comparative work using such paradigms has primarily investigated sequence learning within a single sensory modality. We used an AGL paradigm to evaluate how humans and macaque monkeys learn and respond to identically structured sequences of either auditory or visual stimuli. In the auditory and visual experiments, we found that both species were sensitive to the ordering relationships between elements in the sequences. Moreover, the humans and monkeys produced largely similar response patterns to the visual and auditory sequences, indicating that the sequences are processed in comparable ways across the sensory modalities. These results provide evidence that human sequence processing abilities stem from an evolutionarily conserved capacity that appears to operate comparably across the sensory modalities in both human and nonhuman primates. The findings set the stage for future neurobiological studies to investigate the multisensory nature of these sequencing operations in nonhuman primates and how they compare to related processes in humans.