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What is the connection between the cultural evolution of a language and the rapid processing response to that language in the brains of individual learners? In an iterated communication study that was conducted previously, participants were asked to communicate temporal concepts such as "tomorrow," "day after," "year," and "past" using vertical movements recorded on a touch screen. Over time, participants developed simple artificial 'languages' that used space metaphorically to communicate in nuanced ways about time. Some conventions appeared rapidly and universally (e.g., using larger vertical movements to convey greater temporal durations). Other conventions required extensive social interaction and exhibited idiosyncratic variation (e.g., using vertical location to convey past or future). Here we investigate whether the brain's response during acquisition of such a language reflects the process by which the language's conventions originally evolved. We recorded participants' EEG as they learned one of these artificial space-time languages. Overall, the brain response to this artificial communication system was language-like, with, for instance, violations to the system's conventions eliciting an N400-like component. Over the course of learning, participants' brain responses developed in ways that paralleled the process by which the language had originally evolved, with early neural sensitivity to violations of a rapidly-evolving universal convention, and slowly developing neural sensitivity to an idiosyncratic convention that required slow social negotiation to emerge. This study opens up exciting avenues of future work to disentangle how neural biases influence learning and transmission in the emergence of structure in language.

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]

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]

There is a long-standing debate in cognitive science surrounding the source of commonalities among languages of the world. Indeed, there are many potential explanations for such commonalities—accidents of history, common processes of language change, memory limitations, constraints on linguistic representations, and so on. Recent research has used psycholinguistic experiments to provide empirical evidence linking common linguistic patterns to specific features of human cognition, but these experiments tend to use English speakers, who in many cases have direct experience with the common patterns of interest. Here we highlight the importance of testing populations whose languages go against cross-linguistic trends. We investigate whether adult monolingual speakers of Kîîtharaka, which has an unusual way of ordering words, mirror the word-order preferences of English speakers. We find that they do, supporting the hypothesis that universal cognitive representations play a role in shaping word order. [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]

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.

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]

This study investigates substantive bias, a phenomenon wherein learners exhibit a preference for phonetically motivated patterns in language acquisition. The study presents evidence that variable input, rather than categorical input, can activate substantive bias. Native speakers of Hong Kong Cantonese were randomly assigned to categorical or variable training conditions for vowel backness harmony or disharmony, or to a no-training control condition. Results indicate that participants in the categorical and control conditions did not exhibit a bias towards either pattern. However, participants in the variable conditions displayed a bias towards vowel harmony, suggesting that input variability can strengthen the effect of substantive bias. These findings contribute to our comprehension of the role of input variability in phonological learning and the mechanisms involved in the acquisition of phonetically motivated and unmotivated phonological patterns.

Agreement markers that refer to the same feature or argument tend to be found in the same position (e.g., all subject agreement markers as suffixes, all object agreement markers as prefixes). However, little is known about the exceptions to this trend: cases where different values of the same feature are marked in different positions in the word (i.e., positional splits). In this study, we explore the positional properties of subject and object person-number agreement markers in a phylogenetically diverse sample of 227 languages. We find that the recurrence of a positional split is proportional to its degree of naturalness, that is, to the amount of shared feature values amongst the forms with the same positional arrangement. Natural patterns (e.g., where prefixal forms all share SG and suffixal forms all share PL) are over-represented in natural languages compared to a random baseline. The most unnatural patterns are underrepresented, and splits with an intermediate level of unnaturalness occur at around chance levels. We hypothesise that this graded bias for naturalness is grounded in a preference for morphological similarity amongst semantically similar forms during language learning. To test this hypothesis we conducted two online artificial language learning experiments where we trained and tested participants on person-number verbal agreement paradigms of different sizes with positional splits of different degrees of naturalness. We found that their relative learnability is also gradient, again proportional to the amount of feature value overlap, thus matching the observed cross-linguistic tendencies. Our findings support the notion that semantic similarity shapes the evolution of morphological structure in person-number verbal agreement systems and that it does so in a gradient way.

Sound correspondences (SCs) have been found to be learnable phonological patterns in second dialect acquisition. Cross-linguistically, SCs consist of similar as well as distinct variants. However, in the study of SC learning, the effect of the similarity between the corresponding variants remains understudied. The salience hypothesis proposes that distinct dialect variants are more salient and learnable, while the learning bias hypothesis in phonological learning predicts that SC patterns with similar variants are preferred by learners. We conducted an artificial language learning experiment to test how sound similarity affects SC learning. Specifically, the degrees of similarity between variants were evaluated from multidimensional metrics, including phonetic and phonological measures, which are cross-validated with typological evidence. While there was no effect of variant similarity in learning simple one-to-one SCs, a preference for the most distinct dialect variant was found in the learning of SCs exhibiting more complex mapping structures (i.e., two-to-one and one-to-two). Our results confirm a preference for distinct variants in SC learning, although this effect relies on two conditions. First, the preference for distinction emerges only in the presence of complex mapping structures. Second, this preference requires an activation threshold, in that the distance of the SC must be sufficiently large to trigger the effect. [ABSTRACT FROM AUTHOR]

Artificial language learning research has become a popular tool to investigate universal mechanisms in language learning. However, often it is unclear whether the found effects are due to learning, or due to artefacts of the native language or the artificial language, and whether findings in only one language will generalise to speakers of other languages. The present study offers a new approach to model the influence of both the L1 and the target artificial language on language learning. The idea is to control for linguistic factors of the artificial and the native language by incorporating measures of wordlikeness into the statistical analysis as covariates. To demonstrate the approach, we extend Linzen and Gallagher (2017)’s study on consonant identity pattern to evaluate whether speakers of German and Mandarin rapidly learn the pattern when influences of L1 and the artificial language are accounted for by incorporating measures assessed by analogical and discriminative learning models over the L1 and artificial lexicon. Results show that nonwords are more likely to be accepted as grammatical if they are more similar to the trained artificial lexicon and more different from the L1 and, crucially, the identity effect is still present. The proposed approach is helpful for designing cross-linguistic studies.

Response particles, like English ‘yes’ and ‘no’, are used to respond to polar questions or assertions and are found in all languages. However, the number of particles and the specific meanings they convey vary across languages. For example, in some languages particles mainly convey whether the response itself is positive or negative, while in others they convey whether the response is agreeing or disagreeing with previous discourse. Further, some languages have two response particles, while others have three, or even four. Recent work suggests that how meanings tend to be mapped to forms cross-linguistically might nevertheless be constrained. Roelofsen & Farkas (2015) suggest that indicating disagreement with a negative question or assertion (e.g., A: ‘Ally doesn’t eat meat.’ B: ‘Yes, he does.’) is more marked than indicating agreement with a positive assertion (e.g., A: ‘Ally eats meat.’ B: ‘Yes, he does’.). This difference in semantic markedness is argued to lead to a difference in form: more marked meanings are mapped to more specialized forms. Here we investigate this hypothesis in a series of behavioral experiments. Across our experiments, we find that participants are indeed sensitive to the differences in meaning that particles can convey. However, not all of the differences implicated by the hierarchy hypothesized in Roelofsen & Farkas (2015) are supported by our results, and we find evidence highlighting an unexpected special role for Positive Agreement—the least marked meaning.

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]

• Distinct statistical learning processes drive the link from oral language to reading. • Oral language is predicted by statistical learning to generalise abstract stimuli. • Reading is predicted by statistical learning to generalise via oral language. • Oral language and reading are not predicted by statistical learning to segment speech. • Infant non-adjacent statistical processing predicts childhood language development. Statistical learning ability has been found to relate to children's reading skills. Yet, statistical learning is also known to be vital for developing oral language skills, and oral language and reading skills relate strongly. These connections raise the question of whether statistical learning ability affects reading via oral language or directly. Statistical learning is multifaceted, and so different aspects of statistical learning might influence oral language and reading skills distinctly. In a longitudinal study, we determined how two aspects of statistical learning from an artificial language tested on 70 17-month-old infants—segmenting sequences from speech and generalizing the sequence structure—related to oral language skills measured at 54 months and reading skills measured at approximately 75 months. Statistical learning segmentation did not relate significantly to oral language or reading, whereas statistical learning generalization related to oral language, but only indirectly related to reading. Our results showed that children's early statistical learning ability was associated with learning to read via the children's oral language skills. [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]

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]

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]

We investigated whether learning an artificial language at 17 months was predictive of children's natural language vocabulary and grammar skills at 54 months. Children at 17 months listened to an artificial language containing non-adjacent dependencies, and were then tested on their learning to segment and to generalise the structure of the language. At 54 months, children were then tested on a range of standardised natural language tasks that assessed receptive and expressive vocabulary and grammar. A structural equation model demonstrated that learning the artificial language generalisation at 17 months predicted language abilities – a composite of vocabulary and grammar skills – at 54 months, whereas artificial language segmentation at 17 months did not predict language abilities at this age. Artificial language learning tasks – especially those that probe grammar learning – provide a valuable tool for uncovering the mechanisms driving children's early language development. [ABSTRACT FROM AUTHOR]

While variation occurs in both phonology and morphosyntax, phonological variation also includes phonetic variation motivated by articulatory or perceptual factors. While learning in both domains is subject to cognitive biases, phonological learning may also be biased by physical factors, which may enhance learnability of phonetically motivated alternations. This study aims to identify whether learning differs when children are exposed to phonological or morphosyntactic patterns with equal complexity. Cantonese-speaking children learned an artificial language involving rounding harmony, where unround [e] or round [o] harmonizes with the following noun, or gender agreement, with feminine and masculine allomorphs lo ~ le. Patterns applied variably in 67% of training items, or categorically. Children were tested on generalization to novel stems. In the categorical learning conditions, participants showed comparable rates of harmony/agreement. In the variable phonological learning conditions, application of harmony exceeded the rate of exposure in training, suggesting the influence of a bias toward phonetically grounded rounding harmony. In the variable morphosyntactic condition, participants applied agreement below the rate of exposure. This finding points to a qualitative difference between learning in the two domains, with phonological (but not morphosyntactic) learning influenced by substantive grounding. [ABSTRACT FROM AUTHOR]

• We test the learnability of evidentials using Artificial Language Learning methods. • Cross-linguistically prevalent evidential distinctions are learned more easily. • Same patterns occur when non-linguistic symbols encode evidential meanings. • We propose that pragmatic pressures explain the learnability patterns observed. Cross-linguistically prevalent semantic distinctions are widely assumed to be easier to learn because they reflect natural concepts. Here we propose an alternative, pragmatic perspective that links both the cross-linguistic prevalence and the learnability of semantic distinctions to communicative pressures. We focus on evidentiality (the encoding of the speaker's information source). Across languages, grammatical evidential systems are more likely to encode indirect sources (especially, reported information) compared to direct sources (e.g., visual perception). On a conceptual account, this seems puzzling, since humans reason naturally about how seeing connects to knowing. On a pragmatic account, however, the predominant encoding of the speaker's reportative compared to visual information sources can be explained in terms of informativeness (visual access is ubiquitous and potentially more reliable, hence less marked). We tested the pragmatic account in four experiments. Adult English speakers exposed to novel miniature evidential morphological systems consistently showed higher learning rates for systems with a single indirect (reportative) compared to a single direct (visual) evidential morpheme (Experiment 1). This pattern persisted even when participants were given specific cues to the target meanings (Experiment 2) and partly extended to cases where evidential meanings were conveyed through visual, not linguistic, means (Experiment 3). It also persisted when the evidential morphemes had to be learned from different materials (Experiment 4). We conclude that the cross-linguistic bias to mark reportative/indirect over visual/direct sources of information has pragmatic roots that also shape the learnability of evidential semantic distinctions. [ABSTRACT FROM AUTHOR]