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There is ample evidence that individual‐level cognitive mechanisms active during language learning and use can contribute to the evolution of language. For example, experimental work suggests that learners will reduce case marking in a language where grammatical roles are reliably indicated by fixed word order, a correlation found robustly in the languages of the world. However, such research often assumes homogeneity among language learners and users, or at least does not dig into individual differences in behavior. Yet, it is increasingly clear that language users vary in a large number of ways: in culture, in demographics, and—critically for present purposes—in terms of cognitive diversity. Here, we explore how neurodiversity impacts behavior in an experimental task similar to the one summarized above, and how this behavior interacts with social pressures. We find both similarities and differences between autistic and nonautistic English‐speaking individuals, suggesting that neurodiversity can impact language change in the lab. This, in turn, highlights the potential for future research on the role of neurodivergent populations in language evolution more generally. [ABSTRACT FROM AUTHOR]

A foundational goal of linguistics has been to understand why languages look the way they do. A range of possible explanations exist – from domain-specific representations to cognition-external factors like history and grammaticalization – and all of these undoubtedly play some role. But determining exactly how these link with specific features of language remains challenging, and the role of domain-specific mechanisms has been particularly contentious. In this paper, I highlight a growing new approach, which uses artificial language experiments to link individual-level biases to cross-linguistic trends in language structure. Using word and morpheme order as case studies, I will show how a range of different paradigms and learner populations allow us to make progress on this crucial issue in linguistics. I will focus on typological trends in word and morpheme order. For some ordering trends, experimental evidence points to variation across populations, suggesting that the best explanation for these patterns likely has its root in language history and grammaticalization. In other cases, the evidence points to the role of universal but domain-general cognitive biases, like transparency and simplicity. These domain-general biases interact with linguistic representations in important ways. Taken together these studies help adjudicate between alternative explanations for a number of specific ordering patterns and suggest a new sense of domain-specificity in the evolution of language. [ABSTRACT FROM AUTHOR]

Grammatical redundancy is a widespread feature across languages. Although redundant cues can be seen to increase the complexity and processing burden of structures, it has been suggested that they can assist language acquisition. Here, we explored if this learning benefit can be observed from the very initial stages of second language (L2) acquisition and whether the effect of redundancy is modulated by the perceptual salience of the redundant linguistic cues. Across two experiments, three groups of adult native speakers of English were incidentally exposed to three different artificial languages; one that had a fixed word order, Verb-Object-Subject, and two in which thematic role assignment was additionally determined by a low-salient (Experiment 1) or a high-salient (Experiment 2) redundant case marker. While all groups managed to learn the novel language, our results pointed towards a hindering role of redundancy, with participants in the non-redundant condition achieving greater learning outcomes compared to those in both redundant conditions. Results also revealed that this impeding effect of redundancy on L2 learners can be attenuated by the salience of the redundant cue (Experiment 2). In conjunction with earlier findings, the present results suggest that the effect of redundancy on L2 acquisition can be differentially manifested depending on the stage of L2 development, learners' first language biases and age. [ABSTRACT FROM AUTHOR]

General principles of human cognition can help to explain why languages are more likely to have certain characteristics than others: structures that are difficult to process or produce will tend to be lost over time. One aspect of cognition that is implicated in language use is working memory--the component of short-term memory used for temporary storage and manipulation of information. In this study, we consider the relationship between working memory and regularization of linguistic variation. Regularization is a well-documented process whereby languages become less variable (on some dimension) over time. This process has been argued to be driven by the behavior of individual language users, but the specific mechanism is not agreed upon. Here, we use an artificial language learning experiment to investigate whether limitations in working memory during either language learning or language production drive regularization behavior. We find that taxing working memory during production results in the loss of all types of variation, but the process by which random variation becomes more predictable is better explained by learning biases. A computational model offers a potential explanation for the production effect using a simple self-priming mechanism. [ABSTRACT FROM AUTHOR]

In language learning, learners engage with their environment, incorporating cues from different sources. However, in lab‐based experiments, using artificial languages, many of the cues and features that are part of real‐world language learning are stripped away. In three experiments, we investigated the role of positive, negative, and mixed feedback on the gradual learning of language‐like statistical regularities within an active guessing game paradigm. In Experiment 1, participants received deterministic feedback (100%), whereas probabilistic feedback (i.e., 75% or 50%) was introduced in Experiment 2. Finally, Experiment 3 explored the impact of mixed probabilistic feedback (33% positive, 33% negative, 33% no feedback). The results showed that cross‐situational learning of words was observed without feedback, but participants were able to learn structural regularities of the miniature language only when feedback was provided. Interestingly, the presence of positive feedback was particularly helpful for the learner, promoting more in‐depth learning of the artificial language. [ABSTRACT FROM AUTHOR]

The experimental study of artificial language learning has become a widely used means of investigating the predictions of theories of language learning and representation. Although much is now known about the generalizations that learners make from various kinds of data, relatively little is known about how those representations affect speech processing. This paper presents an event-related potential (ERP) study of brain responses to violations of lab-learned phonotactics. Novel words that violated a learned phonotactic constraint elicited a larger Late Positive Component (LPC) than novel words that satisfied it. Similar LPCs have been found for violations of natively acquired linguistic structure, as well as for violations of other types of abstract generalizations, such as musical structure. We argue that lab-learned phonotactic generalizations are represented abstractly and affect the evaluation of speech in a manner that is similar to natively acquired syntactic and phonological rules. [ABSTRACT FROM AUTHOR]

Inverse probability adaptation effects (the finding that encountering a verb in an unexpected structure increases long-term priming for that structure) have been observed in both L1 and L2 speakers. However, participants in these studies all had established representations of the syntactic structures to be primed. It therefore remains an open question whether inverse probability adaptation effects could take place with newly encountered L2 structures. In a pre-registered experiment, we exposed participants (n = 84) to an artificial language with active and passive constructions. Training on Day 1 established expectations for specific co-occurrence patterns between verbs and structures. On Day 2, established patterns were violated for the surprisal group (n = 42), but not for the control group (n = 42). We observed no immediate priming effects from exposure to high-surprisal items. On Day 3, however, we observed an effect of input variation on comprehension of verb meaning in an auditory grammaticality judgment task. The surprisal group showed higher accuracy for passive structures in both tasks, suggesting that experiencing variation during learning had promoted the recognition of optionality in the target language. [ABSTRACT FROM AUTHOR]

Over the last two decades, the question of to which linguistic cues learners pay attention when they decode a new language has been subject to controversy in the field of third language (L3) acquisition. In this article, we present an artificial language learning experiment that investigated how lexical and syntactic similarities between an artificial L3 and preexisting grammars impact crosslinguistic influence at the very beginning of the acquisition process. We exposed four groups of 30 Norwegian–English bilinguals each to one of four L3s and gave them training in that L3. The participants gave forced‐choice acceptability judgments on pairs of nonsubject‐initial declarative clauses that differed in word order, one grammatical in English, the other grammatical in Norwegian. The participants had not been exposed to nonsubject‐initial declaratives during the exposure and training phases to avoid confounds with learning. The results showed that both lexical and syntactic similarities affect crosslinguistic influence. We discuss this result considering contemporary accounts of L3 acquisition. A one‐page Accessible Summary of this article in non‐technical language is freely available in the Supporting Information online and at https://oasis‐database.org [ABSTRACT FROM AUTHOR]

We investigated the emergence of sociolinguistic indexicality using an artificial‐language‐learning paradigm. Sociolinguistic indexicality involves the association of linguistic variants with nonlinguistic social or contextual features. Any linguistic variant can acquire "constellations" of such indexical meanings, though they also exhibit an ordering, with first‐order indices associated with particular speaker groups and higher‐order indices targeting stereotypical attributes of those speakers. Much natural‐language research has been conducted on this phenomenon, but little experimental work has focused on how indexicality emerges. Here, we present three miniature artificial‐language experiments designed to break ground on this question. Results show ready formation of first‐order indexicality based on co‐occurrence alone, with higher‐order indexicality emerging as a result of extension to new speaker groups, modulated by the perceived practical importance of the indexed social feature. [ABSTRACT FROM AUTHOR]

In traditional, generative phonology, sound patterns are represented in terms of abstract features, typically based on the articulatory properties of the sounds. The present study makes use of an artificial language learning experiment to explore when and how learners extend a novel phonological pattern to novel segments. Adult, English-speaking learners were exposed to a spirantization pattern in which a stop became a fricative between two vowels (e.g., /bib/ + /o/ ➔ [bivo]). Participants were trained on spirantization for two of four possible stop-fricative pairs, and were tested on their generalization to the held-out segments. Two groups of participants were trained on items based on voicing (e.g., the Voiced condition was trained on /b/ ➔ [v], and /d/ ➔ [z], and tested on /p/ ➔ [f], and /t/ ➔ [s]), and two groups of participants were trained on items based on place of articulation (e.g., the Labial condition was trained on /b/ ➔ [v], and /p/ ➔ [f] and tested on /t/ ➔ [s], and /d/ ➔ [z]). Participants in both Place and Voice conditions were successful at learning and generalizing the spirantization pattern to novel segments, but rates of generalization were higher in the Voice conditions. These results support a similarity-based approach to generalization, particularly one that takes into account articulatorily-based features and natural classes. Implications for phonological theory are discussed. [ABSTRACT FROM AUTHOR]

Over half a century ago, George Zipf observed that more frequent words tend to be older. Corpus studies since then have confirmed this pattern, with more frequent words being replaced and regularized less often than less frequent words. Two main hypotheses have been proposed to explain this: that frequent words change less because selection against innovation is stronger at higher frequencies, or that they change less because stochastic drift is stronger at lower frequencies. Here, we report the first experimental test of these hypotheses. Participants were tasked with learning a miniature language consisting of two nouns and two plural markers. Nouns occurred at different frequencies and were subjected to treatments that varied drift and selection. Using a model that accounts for participant heterogeneity, we measured the rate of noun regularization, the strength of selection, and the strength of drift in participant responses. Results suggest that drift alone is sufficient to generate the elevated rate of regularization we observed in low‐frequency nouns, adding to a growing body of evidence that drift may be a major driver of language change. [ABSTRACT FROM AUTHOR]

We report on an artificial language learning experiment testing the learnability of a typologically rare pattern of reduplication. Our model comes from syllable-copy reduplication in Hiaki (aka Yaqui, Uto-Aztecan), a base-dependent pattern wherein the shape of reduplication depends crucially on syllabification in the base: coda consonants can copy in reduplication if and only if there is a corresponding coda in the base. Using a controlled artificial language experiment with a forced-choice paradigm, we show that native English speakers who have no prior exposure to any language with a grammar employing syllable-copy reduplication are in many cases able to learn a variable CV or CVC syllable-copying rule as measured by eventual above-chance selection of the correct form. However, compared to participants learning either a consistent CV or CVC copying rule, the performance of participants tasked with learning such a variable syllable-copying rule improves more slowly, and these participants make more errors overall. We suggest that this difference in learnability may be one of a number of factors helping to explain the typological rarity of certain morphological patterns. [ABSTRACT FROM AUTHOR]

Grammatical regularities may correlate with semantics; e.g. grammatical gender is often partially predictable from the noun's semantics. We explore whether learners generalise over semantic cues, and whether the extent of exposure (1 versus 4 sessions) and number of exemplars for each semantic class (type-frequency) affect this. Six-year-olds and adults were exposed to semi-artificial languages where nouns co-occurred with novel particles, with particle usage fully or partially determined by the semantics of the nouns. Both adults and children generalised to novel nouns when semantic cues were fully consistent. Adults (but not children) also generalised when cues were partially consistent. Generalisation increased with exposure, however there was no evidence that increasing type-frequency (i.e. more nouns per semantic class) increased generalisation. Post-experiment interviews also suggested that successful generalisation depended on explicit awareness. These results suggest that semantic cues are particularly difficult for children to exploit during the early stages of language acquisition. [ABSTRACT FROM AUTHOR]

Person systems convey the roles entities play in the context of speech (e.g., speaker, addressee). As with other linguistic category systems, not all ways of partitioning the person space are equally likely crosslinguistically. Different theories have been proposed to constrain the set of possible person partitions that humans can represent, explaining their typological distribution. This article introduces an artificial language learning methodology to investigate the existence of universal constraints on person systems. We report the results of three experiments that inform these theoretical approaches by generating behavioral evidence for the impact of constraints on the learnability of different person partitions. Our findings constitute the first experimental evidence for learnability differences in this domain. [ABSTRACT FROM AUTHOR]

Many languages exhibit differential object marking (DOM), where only certain types of grammatical objects are marked with morphological cases. Traditionally, it has been claimed that DOM arises as a way to prevent ambiguity by marking objects that might otherwise be mistaken for subjects (e.g., animate objects). While some recent experimental work supports this account, research on language typology suggests at least one alternative hypothesis. In particular, DOM may instead arise as a way of marking objects that are atypical from the point of view of information structure. According to this account, rather than being marked to avoid ambiguity, objects are marked when they are given (already familiar in the discourse) rather than new. Here, we experimentally investigate this hypothesis using two artificial language learning experiments. We find that information structure impacts participants' object marking, but in an indirect way: atypical information structure leads to a change in word order, which then triggers increased object marking. Interestingly, this staged process of change is compatible with documented cases of DOM emergence. We argue that this process is driven by two cognitive tendencies. First, a tendency to place discourse given information before new information, and second, a tendency to mark noncanonical word order. Taken together, our findings provide corroborating evidence for the role of information structure in the emergence of DOM systems. [ABSTRACT FROM AUTHOR]

The present study explores how language learners apply gender stereotypes in learning a novel language with grammatical gender. Adult, English-speaking participants were exposed to picture–sound pairs from a miniature language. Each picture was of a matched gendered professional (e.g., male tennis player, female tennis player) with a nonsense form [CVCV-go/gu]. Participants were exposed to 32 picture–sound pairs (16 male, and 16 female, all matched) five times in a randomized order. Following training, participants were given a two-alternative forced-choice test with novel picture–word pairs. Participants were presented with a novel picture paired with two words (e.g., [befegu vs. befebo]) and were asked to choose which word most likely portrayed the meaning conveyed by the picture. These novel items contained gender-matched professions (e.g., male and female chemist), neutral items (office supplies), stereotypically female items (makeup), and stereotypically male items (tools). Participants assigned the appropriate gender to the novel professions, and assigned gender in line with the stereotyped objects at a rate significantly greater than chance (but not for neutral items). These results support the hypothesis that learning a language with a binary grammatical gender might be influenced by gender stereotypes. [ABSTRACT FROM AUTHOR]

This article examines whether children alter a variable phonological pattern in an artificial language towards a phonetically-natural form. We address acquisition of a variable rounding harmony pattern through the use of two artificial languages; one with dominant harmony pattern, and another with dominant non-harmony pattern. Overall, children favor harmony pattern in their production of the languages. In the language where harmony is non-dominant, children's subsequent production entirely reverses the pattern so that harmony predominates. This differs starkly from adults. Our results compare to the regularization found in child learning of morphosyntactic variation, suggesting a role for naturalness in variable phonological learning. [ABSTRACT FROM AUTHOR]

Inflectional affixes expressing the same grammatical category (e.g., subject agreement) tend to appear in the same morphological position in the word. We hypothesize that this cross‐linguistic tendency toward category clustering is at least partly the result of a learning bias, which facilitates the transmission of morphology from one generation to the next if each inflectional category has a consistent morphological position. We test this in an online artificial language experiment, teaching adult English speakers a miniature language consisting of noun stems representing shapes and suffixes representing the color and number features of each shape. In one experimental condition, each suffix category has a fixed position, with color in the first position and number in the second position. In a second condition, each specific combination of suffixes has a fixed order, but some combinations have color in the first position, and some have number in the first position. In a third condition, suffixes are randomly ordered on each presentation. While the language in the first condition is consistent with the category clustering principle, those in the other conditions are not. Our results indicate that category clustering of inflectional affixes facilitates morphological learning, at least in adult English speakers. Moreover, we found that languages that violate category clustering but still follow fixed affix ordering patterns are more learnable than languages with random ordering. Altogether, our results provide evidence for individual biases toward category clustering; we suggest that this bias may play a causal role in shaping the typological regularities in affix order we find in natural language. [ABSTRACT FROM AUTHOR]

In two artificial language learning experiments with four groups of highly proficient Basque-Spanish bilinguals and two groups of Spanish monolinguals, we examine the cues that allow adult listeners to parse new input into phrases. In addition, we investigate which factors lead bilinguals to switch between the segmentation strategies characteristic of their two languages. We show that segmental information drives bilinguals' choice of a segmentation strategy when presented with an unfamiliar language. The language in which bilinguals are addressed during the study (i.e. the language of context) additionally modulates their segmentation preference, and this context language effect is found in L1Basque bilinguals but does not extend to L1Spanish bilinguals. The cause of this asymmetry is yet to be established. Finally, we show that adult monolinguals disregard statistical cues in favor of unfamiliar segmental information when in conflict. These results evidence that the available phrase segmentation cues are arranged hierarchically. [ABSTRACT FROM AUTHOR]

The present study explores learning phonological alternations that contain exceptions. Participants were exposed to a back/round vowel harmony pattern in which a regular suffix obeyed a vowel harmony rule, varying between /e/ and /o/ depending on the back/round phonetic features of the stem, and a non-alternating suffix that was always /o/ regardless of the features of the stem vowel. Participants in Experiment 1 learned the behavior of both suffixes, but correct performance for the non-alternating suffix was higher when the suffix happened to be in harmony with the stem. Participants in Experiment 2 were exposed to the non-alternating affix in harmonic contexts only, and continued to show a bias towards harmony. Experiment 3 replicated Experiment 2 with minimal training on disharmonic cases of the non-alternating morpheme. However, participants were less likely to learn the alternating affix without exposure to morphological stem, stem + suffix alternations in Experiment 4, suggesting a bias towards morphophonological alternations in learning vowel harmony patterns. [ABSTRACT FROM AUTHOR]

Languages vary with respect to whether sentences with two negative elements give rise to double negation or negative concord meanings. We explore an influential hypothesis about what governs this variation: namely, that whether a language exhibits double negation or negative concord is partly determined by the phonological and syntactic nature of its negative marker (Zeijlstra 2004; Jespersen 1917). For example, one version of this hypothesis argues that languages with affixal negation must be negative concord (Zeijlstra 2008). We use an artificial language learning experiment to investigate whether English speakers are sensitive to the status of the negative marker when learning double negation and negative concord languages. Our findings fail to provide evidence supporting this hypothesised connection. Instead, our results suggest that learners find it easier to learn negative concord languages compared to double negation languages independently of whether the negative marker is an adverb or an affix. This is in line with evidence from natural language acquisition (Thornton et al. 2016). [ABSTRACT FROM AUTHOR]

We investigated L1 and L2 frequency effects in the sharing of syntax across languages (reflected in cross-linguistic structural priming) using an artificial language (AL) paradigm. Ninety-six Dutch speakers learned an AL with either a prepositional-object (PO) dative bias (PO datives appeared three times as often as double-object [DO] datives) or a DO dative bias (DOs appeared three times as often as POs). Priming was assessed from the AL to Dutch (a strongly PO-biased language). There was weak immediate priming for DOs, but not for POs in both bias conditions. This suggests that L1, but not AL, frequency influenced immediate priming. Furthermore, the DO bias group produced 10% more DOs in Dutch than the PO bias group, showing that cumulative priming was influenced by AL frequency. We discuss the different effects of L1 and AL frequency on cross-linguistic structural priming in terms of lexicalist and implicit learning accounts. [ABSTRACT FROM AUTHOR]

Experience with native-language prosody encourages language-specific strategies for speech segmentation. Conflicting findings from previous research suggest that these strategies may not be abstracted away from the acoustic manifestation of prosodic features in the native speech. Using the artificial language learning paradigm, the current study explores this possibility in connection with listeners of a lexical tone language called Taiwanese Southern Min (TSM). In TSM, the only rising lexical tone occurs almost only on the final syllable of the language's tone sandhi domain and is phonetically associated with final lengthening. Based on these observations, Experiment I examined what constituted a sufficient finality cue for use by TSM listeners to support segmentation: (a) final fundamental frequency (F0) rise only; or (b) final F0 rise conjoined with final lengthening. The results showed that segmentation was inhibited by the former cue but facilitated by the latter. Experiment II showed that the facilitation cannot be attributed entirely to final lengthening, as a null effect was found when final lengthening was the sole prosodic cue to segmentation. It is thus assumed that acoustic details as fine-grained as the lengthening of the rising tone are involved in the modulation of the segmentation strategy whereby TSM listeners perceive F0 rise as signaling finality. The inhibitory effect of final F0 rise alone found in Experiment I motivated Experiment III, which revealed that initial F0 rise in the absence of lengthening cues improved TSM listeners' segmentation. It is speculated that such use of initial F0 rise might reflect a cross-linguistic segmentation solution. [ABSTRACT FROM AUTHOR]

Many studies suggest that detecting statistical regularities in linguistic input plays a key role in language acquisition. Although statistical learning is not necessarily implicit in nature, it is often defined as learning that happens without awareness. This article investigates whether statistical learning in young children is indeed implicit, as often assumed. We trained 63 kindergarteners on a miniature language and assessed learning using a picture‐matching task. We used an opt‐out task to measure whether the kindergarteners possessed awareness of an acquired meaningful grammatical marker. In the opt‐out paradigm, participants demonstrate awareness by expressing uncertainty through a nonverbal response: opting out. Our results are compatible with an earlier study of which the present study is a partial replication, suggesting that kindergarteners can acquire this marker from distributional properties in the input. Furthermore, although none of the children could verbalize knowledge of the structure during exit interviews, their behavior during the opt‐out task indicated that they developed awareness of it. [ABSTRACT FROM AUTHOR]

Tonal carryover assimilation, whereby a tone is assimilated to the preceding one, is conditioned by prosodic boundaries in a way suggesting that its presence may signal continuity or lack of a boundary. Its possibility as a speech segmentation cue was investigated in two artificial language (AL) learning experiments. Mandarin-speaking listeners identified the "words" of a three-tone AL (e.g., [pé.tī.kù]) after listening to six long speech streams in which the words were repeated continuously without pauses. The first experiment revealed that segmentation was disrupted in an "incongruent-cues" condition where tonal carryover assimilation occurred across AL word boundaries and conflicted with statistical regularities in the speech streams. Segmentation was neither facilitated nor inhibited in a "congruent-cues" condition where tonal carryover assimilation occurred only within the AL words in 27% of the repetitions and never across word boundaries. A null effect was again found for the congruent-cues condition of the second experiment, where all AL word repetitions carried tonal carryover assimilation. These findings show that tonal carryover assimilation is exploited to resolve segmentation problems when cues conflict. Its null effect in the congruent-cues conditions might be linked to cue redundancy and suggest that it is weighted low in the segmentation cue hierarchy. [ABSTRACT FROM AUTHOR]

Multiword units play an important role in language learning and use. It was proposed that learning from such units can facilitate mastery of certain grammatical relations, and that children and adults differ in their use of multiword units during learning, contributing to their varying language-learning trajectories. Accordingly, adults learn gender agreement better when encouraged to learn from multiword units. Previous work has not examined two core predictions of this proposal: (1) that children also benefit from initial exposure to multiword units, and (2) that their learning patterns reflect a greater reliance on multiword units compared to adults. We test both predictions using an artificial-language. As predicted, both children and adults benefit from early exposure to multiword units. In addition, when exposed to unsegmented input – adults show better learning of nouns compared to article-noun pairings, but children do not, a pattern consistent with adults' predicted tendency to focus less on multiword units. [ABSTRACT FROM AUTHOR]

General vowel harmony and disharmony rules have comparable formal complexity but differ dramatically in typological frequency and phonetic motivation. Previous studies found no difference in learning between vowel harmony and disharmony; this putative equivalence has been used to discount the view that learners are influenced by substantive learning biases. In the current study, we use a more nuanced test to show that there is a clear difference in learning between vowel harmony and disharmony: learners readily infer a vowel harmony pattern, but not a disharmony pattern. The findings suggest that vowel disharmony is in fact strongly disfavored during learning. [ABSTRACT FROM AUTHOR]

Phonological alternations often happen to conform to phonotactic regularities, from which a single mechanism for phonotactics and alternations has been claimed. We note, however, that empirical evidence supporting the link between phonotactics and alternations comes only from English native speakers whose first language (L1) does exhibit phonotactically motivated alternation patterns. This article examines whether the link between phonotactics and alternations is universally available. To do so, we test learning of phonotactics and alternations with Cantonese native speakers, whose L1 provides no evidence for or against the link. We address learning of a vowel harmony pattern through the use of three artificial languages; one with a harmony pattern both within and across stems, another with a harmony pattern only across stems; and the other with a disharmony pattern within stems but harmony across stems. Learners successfully acquired harmony phonotactics according to input patterns, but they showed no difference in learning alternation patterns across the three languages. Our results suggest that the link between phonotactics and alternations might be language-specific: Only upon receiving L1 evidence, learners can use a unified mechanism to encode phonotactics and alternations. [ABSTRACT FROM AUTHOR]

Over the last decade, iterated learning studies have provided compelling evidence for the claim that linguistic structure can emerge from non‐structured input, through the process of transmission. However, it is unclear whether individuals differ in their tendency to add structure, an issue with implications for understanding who are the agents of change. Here, we identify and test two contrasting predictions: The first sees learning as a pre‐requisite for structure addition, and predicts a positive correlation between learning accuracy and structure addition, whereas the second maintains that it is those learners who struggle with learning and reproducing their input who add structure to it. This prediction is hard to test in standard iterated learning paradigms since each learner is exposed to a different input, and since structure and accuracy are computed using the same test items. Here, we test these contrasting predictions in two experiments using a one‐generation artificial language learning paradigm designed to provide independent measures of learning accuracy and structure addition. Adults (N = 48 in each study) were exposed to a semi‐regular language (with probabilistic structure) and had to learn it: Learning was assessed using seen items, whereas structure addition was calculated over unseen items. In both studies, we find a strong positive correlation between individuals' ability to learn the language and their tendency to add structure to it: Better learners also produced more structured languages. These findings suggest a strong link between learning and generalization. We discuss the implications of these findings for iterated language models and theories of language change more generally. [ABSTRACT FROM AUTHOR]

There is a rich tradition of building computational models in cognitive science, but modeling, theoretical, and experimental research are not as tightly integrated as they could be. In this paper, we show that computational techniques—even simple ones that are straightforward to use—can greatly facilitate designing, implementing, and analyzing experiments, and generally help lift research to a new level. We focus on the domain of artificial grammar learning, and we give five concrete examples in this domain for (a) formalizing and clarifying theories, (b) generating stimuli, (c) visualization, (d) model selection, and (e) exploring the hypothesis space. [ABSTRACT FROM AUTHOR]

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 language versions in a between‐subjects design. Priming was assessed between Dutch (no overt case marking, SVO word order) and a) an SVO order version, b) a case marking version, and c) an SOV order version. Similar within‐language and cross‐linguistic priming was found in all versions for transitives, indicating that cross‐linguistic structural priming was not hindered. In contrast, for ditransitives we found similar within‐language priming for all versions, but no cross‐linguistic priming. The finding that cross‐linguistic priming is possible between languages that vary in morphological marking or word order, is compatible with studies showing cross‐linguistic priming between natural languages that differ on these dimensions. [ABSTRACT FROM AUTHOR]

There is substantial debate around the nature of letter position coding in reading. Research on a variety of Indo-European languages suggests uncertainty in position coding; for example, readers perceive transposed-letter stimuli (jugde) as similar to their base words (judge). However, these effects are not apparent for all languages. We developed a powerful new method to delineate how specific properties of a writing system shape the representation of letter position. Two groups of 24 adults learned to read novel words printed in artificial scripts. One group learned a dense orthography (i.e. with many anagrams) and one group learned a sparse orthography (i.e. no anagrams). Following four days of training, participants showed a larger transposed-letter effect in the sparse orthography than in the dense orthography. These results challenge existing models of orthographic processing in reading, and support the claim that orthographic representations are shaped by the nature of the writing system. [ABSTRACT FROM AUTHOR]

Statistical learning (SL) involving sensitivity to distributional regularities in the environment has been suggested to be an important factor in many aspects of cognition, including language. However, the degree to which statistically-learned information is retained over time is not well understood. To establish whether or not learners are able to preserve such regularities over time, we examined performance on an artificial second language learning task both immediately after training and also at a follow-up session 2 weeks later. Participants were exposed to an artificial language (Brocanto2), half of them receiving simplified training items in which only 20% of sequences contained complex structures, whereas the other half were exposed to a training set in which 80% of the items were composed of complex sequences. Overall, participants showed signs of learning at the first session and retention at the second, but the degree of learning was affected by the nature of the training they received. Participants exposed to the simplified input outperformed those in the more complex training condition. A GLMM was used to model the relationship between stimulus properties and participants' endorsement strategies across both sessions. The results indicate that participants in the complex training condition relied more on an item's chunk strength than those in the simple training condition. Taken together, this set of findings shows that statistically learned regularities are retained over the course of 2 weeks. The results also demonstrate that training on input featuring simple items leads to improved learning and retention of grammatical regularities. [ABSTRACT FROM AUTHOR]

Noun phrase word order varies cross-linguistically, however, two distributional asymmetries have attracted substantial attention. First, the most common orders place adjectives closest to the noun, then numerals, then demonstratives (e.g., N-Adj-Num-Dem). Second, exceptions to this are restricted to post-nominal position (e.g., N-Dem-Num-Adj, but not, for instance, Adj-Num-Dem-N). These observations have been argued to reflect constraints on cognition. Here we report on two experiments, providing support for this claim. We taught English- and Thai-speaking participants artificial languages in which the position of modifiers relative to the noun differed from their native order (post-nominal position in English, pre-nominal in Thai). We trained participants on single-modifier phrases, and asked them to extrapolate to multiple modifier phrases. We found that both populations infer relative orders of modifiers that conform to the tendency for closest proximity of adjectives, then numerals, then demonstratives. Further, we show that Thai participants, learning pre-nominal modifiers, exhibit a stronger such preference. These results track the typology closely and are consistent with the claim that noun phrase word order reflects properties of human cognition. We discuss future research needed to rule out alternative explanations for our findings, including prior language experience. [ABSTRACT FROM AUTHOR]

Noun phrase word order varies cross-linguistically, however, two distributional asymmetries have attracted substantial attention. First, the most common orders place adjectives closest to the noun, then numerals, then demonstratives (e.g., N-Adj-Num-Dem). Second, exceptions to this are restricted to post-nominal position (e.g., N-Dem-Num-Adj, but not, for instance, Adj-Num-Dem-N). These observations have been argued to reflect constraints on cognition. Here we report on two experiments, providing support for this claim. We taught English- and Thai-speaking participants artificial languages in which the position of modifiers relative to the noun differed from their native order (post-nominal position in English, pre-nominal in Thai). We trained participants on single-modifier phrases, and asked them to extrapolate to multiple modifier phrases. We found that both populations infer relative orders of modifiers that conform to the tendency for closest proximity of adjectives, then numerals, then demonstratives. Further, we show that Thai participants, learning pre-nominal modifiers, exhibit a stronger such preference. These results track the typology closely and are consistent with the claim that noun phrase word order reflects properties of human cognition. We discuss future research needed to rule out alternative explanations for our findings, including prior language experience. [ABSTRACT FROM AUTHOR]

This study examines how French listeners segment and learn new words of artificial languages varying in the presence of different combinations of sublexical segmentation cues. The first experiment investigated the contribution of three different types of sublexical cues (acoustic-phonetic, phonological and prosodic cues) to word learning. The second experiment explored how participants specifically exploited sublexical prosodic cues. Whereas complementary cues signaling word-initial and word-final boundaries had synergistic effects on word learning in the first experiment, the two manipulated prosodic cues redundantly signaling word-final boundaries in the second experiment were rank-ordered with final pitch variations being more weighted than final lengthening. These results are discussed in light of the notions of cue type, cue position and cue efficiency. [ABSTRACT FROM AUTHOR]

In evolutionary linguistics, experiments using artificial signal spaces are being used to investigate the emergence of speech structure. These signal spaces need to be continuous, non-discretized spaces from which discrete units and patterns can emerge. They need to be dissimilar from—but comparable with—the vocal tract, in order to minimize interference from pre-existing linguistic knowledge, while informing us about language. This is a hard balance to strike. This article outlines a new approach that uses the Leap Motion, an infrared controller that can convert manual movement in 3d space into sound. The signal space using this approach is more flexible than signal spaces in previous attempts. Further, output data using this approach is simpler to arrange and analyze. The experimental interface was built using free, and mostly open- source libraries in Python.We provide our source code for other researchers as open source. [ABSTRACT FROM AUTHOR]

We investigate the learning of contextual meaning by adults in an artificial language. Contextual meaning here refers to the non-denotative contextual information that speakers attach to a linguistic construction. Through a series of short games, played online, we test how well adults can learn different contextual meanings for a word-formation pattern in an artificial language. We look at whether learning contextual meanings depends on the social salience of the context, whether our players interpret these contexts generally, and whether the learned meaning is generalized to new words. Our results show that adults are capable of learning contextual meaning if the context is socially salient, coherent, and interpretable. Once a contextual meaning is recognized, it is readily generalized to related forms and contexts. [ABSTRACT FROM AUTHOR]

Psychological experiments have revealed that in normal visual perception of humans, color cues are more salient than shape cues, which are more salient than textural patterns.We carried out an artificial language learning experiment to study whether such perceptual saliency hierarchy (color > shape > texture) influences the learning of orders regulating adjectives of involved visual features in a manner either congruent (expressing a salient feature in a salient part of the form) or incongruent (expressing a salient feature in a less salient part of the form) with that hierarchy. Results showed that within a few rounds of learning participants could learn the compositional segments encoding the visual features and the order between them, generalize the learned knowledge to unseen instances with the same or different orders, and show learning biases for orders that are congruent with the perceptual saliency hierarchy. Although the learning performances for both the biased and unbiased orders became similar given more learning trials, our study confirms that this type of individual perceptual constraint could contribute to the structural configuration of language, and points out that such constraint, as well as other factors, could collectively affect the structural diversity in languages. [ABSTRACT FROM AUTHOR]

Artificial language learning ( ALL) experiments have become an important tool in exploring principles of language and language learning. A persistent question in all of this work, however, is whether ALL engages the linguistic system and whether ALL studies are ecologically valid assessments of natural language ability. In the present study, we considered these questions by examining the relationship between performance in an ALL task and second language learning ability. Participants enrolled in a Spanish language class were evaluated using a number of different measures of Spanish ability and classroom performance, which was compared to IQ and a number of different measures of ALL performance. The results show that success in ALL experiments, particularly more complex artificial languages, correlates positively with indices of L2 learning even after controlling for IQ. These findings provide a key link between studies involving ALL and our understanding of second language learning in the classroom. [ABSTRACT FROM AUTHOR]

OCP-Place, a cross-linguistically well-attested constraint against pairs of consonants with shared [place], is psychologically real. Studies have shown that the processing of words violating OCP-Place is inhibited. Functionalists assume that OCP arises as a consequence of low-level perception: a consonant following another with the same [place] cannot be faithfully perceived as an independent unit. If functionalist theories were correct, then lexical access would be inhibited if two homorganic consonants conjoin at word boundaries—a problem that can only be solved with lexical feedback.Here, we experimentally challenge the functional account by showing that OCP-Place can be used as a speech segmentation cue during pre-lexical processing without lexical feedback, and that the use relates to distributions in the input.In Experiment 1, native listeners of Dutch located word boundaries between two labials when segmenting an artificial language. This indicates a use of OCP-Labial as a segmentation cue, implying a full perception of both labials. Experiment 2 shows that segmentation performance cannot solely be explained by well-formedness intuitions. Experiment 3 shows that knowledge of OCP-Place depends on language-specific input: in Dutch, co-occurrences of labials are under-represented, but co-occurrences of coronals are not. Accordingly, Dutch listeners fail to use OCP-Coronal for segmentation. [ABSTRACT FROM PUBLISHER]

Several theoretical proposals for the evolution of language have sparked a renewed search for comparative data on human and non-human animal computational capacities. However, conceptual confusions still hinder the field, leading to experimental evidence that fails to test for comparable human competences. Here we focus on two conceptual and methodological challenges that affect the field generally: 1) properly characterizing the computational features of the faculty of language in the narrow sense; 2) defining and probing for human language-like computations via artificial language learning experiments in non-human animals. Our intent is to be critical in the service of clarity, in what we agree is an important approach to understanding how language evolved. [ABSTRACT FROM AUTHOR]

According to classical arguments, language learning is both facilitated and constrained by cognitive biases. These biases are reflected in linguistic typology-the distribution of linguistic patterns across the world's languages-and can be probed with artificial grammar experiments on child and adult learners. Beginning with a widely successful approach to typology (Optimality Theory), and adapting techniques from computational approaches to statistical learning, we develop a Bayesian model of cognitive biases and show that it accounts for the detailed pattern of results of artificial grammar experiments on noun-phrase word order (Culbertson, Smolensky, & Legendre, 2012). Our proposal has several novel properties that distinguish it from prior work in the domains of linguistic theory, computational cognitive science, and machine learning. This study illustrates how ideas from these domains can be synthesized into a model of language learning in which biases range in strength from hard (absolute) to soft (statistical), and in which language-specific and domain-general biases combine to account for data from the macro-level scale of typological distribution to the micro-level scale of learning by individuals. [ABSTRACT FROM AUTHOR]

Musical learning and training appear to have large cross-domain transfer effects: they are beneficial in various cognitive domains including language. The present study aimed to examine the role of musical expertise in how musical and linguistic information contained in songs is used. However, as the superiority of musicians could be attributed to improvements in executive functions (e.g., Bialystok & DePape, 2009), we tried to isolate the role of musical training by comparing music experts to both non-experts and language experts. To this end we used the tasks proposed by Schön and colleagues (2008), who compared artificial language learning (ALL) based on spoken sequences to ALL based on sung sequences. These authors concluded that songs, more than speech, allow fast and strong learning. In contrast to Schön et al. (2008), the benefit of ALL based on songs was not found among non-experts in our study. However, there was a highly significant interaction between type of expertise and materials. The music experts were the only group to benefit from the matching of linguistic and musical information, hence showing a different profile than language experts. The present data thus confirm the specificity of transfer effects linked to musical expertise. [ABSTRACT FROM PUBLISHER]

In this article, we develop a hierarchical Bayesian model of learning in a general type of artificial language-learning experiment in which learners are exposed to a mixture of grammars representing the variation present in real learners' input, particularly at times of language change. The modeling goal is to formalize and quantify hypothesized learning biases. The test case is an experiment (Culbertson, Smolensky, & Legendre, 2012) targeting the learning of word-order patterns in the nominal domain. The model identifies internal biases of the experimental participants, providing evidence that learners impose (possibly arbitrary) properties on the grammars they learn, potentially resulting in the cross-linguistic regularities known as typological universals. Learners exposed to mixtures of artificial grammars tended to shift those mixtures in certain ways rather than others; the model reveals how learners' inferences are systematically affected by specific prior biases. These biases are in line with a typological generalization-Greenberg's Universal 18-which bans a particular word-order pattern relating nouns, adjectives, and numerals. [ABSTRACT FROM AUTHOR]

There exists a fundamental paradox in linguistic cognition. Experiments show consistent sound-symbolic biases in people's processing of artificial words, yet the biases are not manifest in the structure of real words. To address this paradox, we designed an experiment to test the magnitude and source of these biases. Participants were tasked with matching nonsense words to novel object forms. One group was implicitly taught a matching rule congruent with biases reported previously, while a second group was taught a rule incongruent with this bias. In test trials, participants in the congruent condition performed only modestly but significantly better than chance and better than participants in the incongruent condition who performed at chance. These outcomes indicate the processing bias is real but weak and reflects an inherent learning bias. We discuss implications for language learning and transmission, considering the functional value of non-arbitrariness in language structure and underlying neurocognitive mechanisms. [ABSTRACT FROM AUTHOR]