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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.

This is the preregistration for Experiment2 of Harmony Block. The predictions are essentially the same, because the changes in the design hopefully will avoid some of the issues in learnability for the patterns

Syntax famously consists of abstract hierarchical representations, essentially instructions for combining words into larger units like sentences. Less famously, most theories of syntax also assume a higher level of abstract representation. Representations at this level comprise instructions for creating the hierarchical representations used to create sentences. To date, however there is no experimental evidence for this additional level of abstraction. Here, we explain why the existence of such representations would imply that, under certain circumstances, speakers should be able to produce structures they have never been exposed to, and we test this prediction directly. We ask: Given the right type of input, can speakers learn a syntactic structure without direct exposure? In particular, different types of relative clauses have different surface word orders. These may be represented in two ways: with many individual representations or one general representation. If the latter, then learning one type of relative clause amounts to learning all types. We teach participants a novel grammar for only some relative clause types (e.g., just subject relative clauses) and test their knowledge of other types (e.g., object relative clauses). Across experiments, participants consistently produced untrained types, implicating the existence of this higher level of abstract syntactic knowledge.

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.

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.

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.

A central question in language acquisition is how children master sentence types that they have seldom, if ever, heard. Here we report the findings of a pre-registered, randomised, single-blind intervention study designed to test the prediction that, for one such sentence type, complex questions (e.g., Is the crocodile who’s hot eating?), children could combine schemas learned, on the basis of the input, for complex noun phrases (the [THING] who’s [PROPERTY]) and simple questions (Is [THING] [ACTION]ing?) to yield a complex-question schema (Is [the [THING] who’s [PROPERTY]] ACTIONing?). Children aged 4;2 to 6;8 (M = 5;6, SD = 7.7 months) were trained on simple questions (e.g., Is the bird cleaning?) and either (Experimental group, N = 61) complex noun phrases (e.g., the bird who’s sad) or (Control group, N = 61) matched simple noun phrases (e.g., the sad bird). In general, the two groups did not differ on their ability to produce novel complex questions at test. However, the Experimental group did show (a) some evidence of generalising a particular complex NP schema (the [THING] who’s [PROPERTY] as opposed to the [THING] that’s [PROPERTY]) from training to test, (b) a lower rate of auxiliary-doubling errors (e.g., *Is the crocodile who’s hot is eating?), and (c) a greater ability to produce complex questions on the first test trial. We end by suggesting some different methods – specifically artificial language learning and syntactic priming – that could potentially be used to better test the present account.

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).

This article reviews work that has employed artificial languages to investigate the learning and processing of additional language grammar in bilinguals, with a focus on morphosyntactic processing in sentence contexts. The article first discusses research that has utilized artificial languages to elucidate two central issues in research on bilingual third language learning and processing: the role of prior language-learning experience and cross-linguistic transfer from the native and second languages to the third. Then, research that has compared bilingual third language to monolingual second language grammar processing is discussed, with specific consideration of hypothesized bilingual advantages at language learning. Finally, future directions in artificial language learning research on bilingual morphosyntactic processing are considered.

We present a critical review of computational models of generalization of simple grammar-like rules, such as ABA and ABB. In particular, we focus on models attempting to account for the empirical results of Marcus et al. (Science, 283(5398), 77–80 1999). In that study, evidence is reported of generalization behavior by 7-month-old infants, using an Artificial Language Learning paradigm. The authors fail to replicate this behavior in neural network simulations, and claim that this failure reveals inherent limitations of a whole class of neural networks: those that do not incorporate symbolic operations. A great number of computational models were proposed in follow-up studies, fuelling a heated debate about what is required for a model to generalize. Twenty years later, this debate is still not settled. In this paper, we review a large number of the proposed models. We present a critical analysis of those models, in terms of how they contribute to answer the most relevant questions raised by the experiment. After identifying which aspects require further research, we propose a list of desiderata for advancing our understanding on generalization.

A foundational goal of linguistics is to investigate whether shared features of the human cognitive system can explain how linguistic patterns are distributed across languages. In this paper we report a series of artificial language learning experiments which aim to test a hypothesised link between cognition and a persistent regularity of morpheme order: number morphemes (e.g., plural markers) tend to be ordered closer to noun stems than case morphemes (e.g., accusative markers) (Universal 39; Greenberg, 1963). We argue that this typological tendency may be driven by learners’ bias towards orders that reflect scopal relationships in morphosyntactic and semantic composition (Bybee, 1985; Rice, 2000; Culbertson & Adger, 2014). This bias is borne out by our experimental results: learners—in the absence of any evidence on how to order number and case morphology—consistently produce number closer to the noun stem. We replicate this effect across two populations (English and Japanese speakers). We also find that it holds independent of morpheme position (prefixal or suffixal), degree of boundedness (free or bound morphology), frequency, and which particular case/number feature values are instantiated in the overt markers (accusative or nominative, plural or singulative). However, we show that this tendency can be reversed when the form of the case marker is made highly dependent on the noun stem, suggesting an influence of an additional bias for local dependencies. Our results provide evidence that universal features of cognition may play a causal role in shaping the relative order of morphemes.

Highlights • Transition between developmental stages of non-adjacent dependency (NAD) learning. • Children between 1 and 3 years of age showed learning of NADs in a foreign language. • Brain responses revealed associative NAD learning, triggered by passive listening. • Gradual decrease of the strength of associative non-adjacent dependency learning., In order to become proficient native speakers, children have to learn the morpho-syntactic relations between distant elements in a sentence, so-called non-adjacent dependencies (NADs). Previous research suggests that NAD learning in children comprises different developmental stages, where until 2 years of age children are able to learn NADs associatively under passive listening conditions, while starting around the age of 3–4 years children fail to learn NADs during passive listening. To test whether the transition between these developmental stages occurs gradually, we tested children’s NAD learning in a foreign language using event-related potentials (ERPs). We found ERP evidence of NAD learning across the ages of 1, 2 and 3 years. The amplitude of the ERP effect indexing NAD learning, however, decreased with age. These findings might indicate a gradual transition in children’s ability to learn NADs associatively. Cognitively, this transition might be driven by children’s increasing knowledge of their native language, hindering NAD learning in novel contexts. Neuroanatomically, maturation of the prefrontal cortex might play a crucial role, promoting top-down learning, affecting bottom-up, associative learning. In sum, our study suggests that NAD learning under passive listening conditions undergoes a gradual transition between different developmental stages during early childhood.

Word order harmony describes the tendency, found across the world’s languages, to consistently order syntactic heads relative to dependents. It is one of the most well-known and well-studied typological universals. Almost since it was first noted by Greenberg (1963), there has been disagreement about what role, if any, the cognitive system plays in driving harmony. Recently, a series of studies using artificial language learning experiments reported that harmonic noun phrase word orders were preferred over non-harmonic orders by English-speaking adults and children (Culbertson et al. 2012, Culbertson & Newport 2015, 2017). However, this evidence is potentially confounded by the fact that English is itself a harmonic language (Goldberg 2013). Here we sought to extend the results from these studies by exploring whether learners who have substantial experience with a non-harmonic language still showed a bias for harmonic patterns during learning. We found that monolingual French- and Hebrew-speaking children, whose language has a non-harmonic noun phrase order (N Adj, Num N) nevertheless preferred harmonic patterns when learning an artificial language. We also found evidence for a harmony bias across several populations of adult learners, although this interacted in complex ways with their L2 experience. Our results suggest that transfer from the L1 cannot explain the preference for harmony found in previous studies. Moreover, they provide the strongest evidence yet that a cognitive bias for harmony is a plausible candidate for shaping linguistic typology.

Recent work has used artificial language experiments to argue that hierarchical representations drive learners’ expectations about word order in complex noun phrases like these two green cars (Culbertson & Adger 2014; Martin, Ratitamkul, et al. 2019). When trained on a novel language in which individual modifiers come after the Noun, English speakers overwhelmingly assume that multiple nominal modifiers should be ordered such that Adjectives come closest to the Noun, then Numerals, then Demonstratives (i.e., N-Adj-Num-Dem or some subset thereof). This order transparently reflects a constituent structure in which Adjectives combine with Nouns to the exclusion of Numerals and Demonstratives, and Numerals combine with Noun+Adjective units to the exclusion of Demonstratives. This structure has also been claimed to derive frequency asymmetries in complex noun phrase order across languages (e.g., Cinque 2005). However, we show that features of the methodology used in these experiments potentially encourage participants to use a particular metalinguistic strategy that could yield this outcome without implicating constituency structure. Here, we use a more naturalistic artificial language learning task to investigate whether the preference for hierarchy-respecting orders is still found when participants do not use this strategy. We find that the preference still holds, and, moreover, as Culbertson & Adger (2014) speculate, that its strength reflects structural distance between modifiers. It is strongest when ordering Adjectives relative to Demonstratives, and weaker when ordering Numerals relative to Adjectives or Demonstratives relative to Numerals. Our results provide the strongest evidence yet for the psychological influence of hierarchical structure on word order preferences during learning.

There is strong scientific consensus that emphasizing print-to-sound relationships is critical when learning to read alphabetic languages. Nevertheless, reading instruction varies across English-speaking countries, from intensive phonic training to multicuing environments that teach sound- and meaning-based strategies. We sought to understand the behavioral and neural consequences of these differences in relative emphasis. We taught 24 English-speaking adults to read 2 sets of 24 novel words (e.g., /buv/, /sig/), written in 2 different unfamiliar orthographies. Following pretraining on oral vocabulary, participants learned to read the novel words over 8 days. Training in 1 language was biased toward print-to-sound mappings while training in the other language was biased toward print-to-meaning mappings. Results showed striking benefits of print-sound training on reading aloud, generalization, and comprehension of single words. Univariate analyses of fMRI data collected at the end of training showed that print-meaning relative to print-sound relative training increased neural effort in dorsal pathway regions involved in reading aloud. Conversely, activity in ventral pathway brain regions involved in reading comprehension was no different following print-meaning versus print-sound training. Multivariate analyses validated our artificial language approach, showing high similarity between the spatial distribution of fMRI activity during artificial and English word reading. Our results suggest that early literacy education should focus on the systematicities present in print-to-sound relationships in alphabetic languages, rather than teaching meaning-based strategies, in order to enhance both reading aloud and comprehension of written words. (PsycINFO Database Record

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 listener...

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.

Previous research on the acquisition of noun classification systems (e.g., grammatical gender)has found that child learners rely disproportionately on phonological cues to determine the class of a new noun, even when competing semantic cues are more reliable in their language.Culbertson, Gagliardi, and Smith (2017) use artificial language learning experiments with adults to argue that this likely results from the early availability of phonological information during acquisition. Learners base their initial representations on formal features of nouns, only later integrating semantic cues from noun meanings. Here, we use these same methods to show that early availability affects cue use in children (6-7 year-olds) as well. However, we also find evidence of developmental changes in sensitivity to semantics; when both cues types are simultaneously available, children are more likely to rely on phonology than adults. Our results suggest that early availability and a bias favoring phonological cues both contribute to children’s over-reliance on phonology in natural language acquisition.

Traditionally, learning is assumed to take place with exposure to simpler elements first followed by exposure to elements with increasing levels of difficulty. Recent reports suggest that exposure to complex elements leads to more widespread changes. However, whether learning via exposure to complex or to simple elements is more beneficial is a matter of ongoing debate. In the current study, using behavioral and electrophysiological measures, we aimed at understanding this by comparing subjects trained with complex speech sounds with those trained with simple speech sounds in a 5-day pseudoword-picture training paradigm. We found that though the subjects learned both complex and simple speech sounds to similar degrees, subjects who were trained with complex stimuli demonstrated more generalizations to novel complex and simple stimuli, whereas those trained with simple stimuli exhibited generalization only to simple but not to complex stimuli (Experiment 1). Along with behavioral measures, using mismatch negativity, we found that training with complex stimuli can lead to more extensive neural changes for both complex and simple stimuli as compared with training with simple stimuli (Experiment 2). In artificial language learning, learning with complex stimuli appears to be more effective than training with simple stimuli as far as generalization is concerned. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Non-adjacent dependencies are ubiquitous in language, but difficult to learn in artificial language experiments in the lab. Previous research suggests that non-adjacent dependencies are more learnable given structural support in the input - for instance, in the presence of high variability between dependent items. However, not all non-adjacent dependencies occur in supportive contexts. How are such regularities learned? One possibility is that learning one set of non-adjacent dependencies can highlight similar structures in subsequent input, facilitating the acquisition of new non-adjacent dependencies that are otherwise difficult to learn. In three experiments, we show that prior exposure to learnable non-adjacent dependencies - i.e., dependencies presented in a learning context that has been shown to facilitate discovery - improves learning of novel non-adjacent regularities that are typically not detected. These findings demonstrate how the discovery of complex linguistic structures can build on past learning in supportive contexts.

Of the 24 possible orderings of the nominal modifiers Demonstrative, Numeral, Adjective and the Noun, two specific patterns dominate the typology: Dem Num Adj N (as in English) and its mirror order N Adj Num Dem (as in Thai). This has been argued to follow from a universal underlying structure in which Adj forms a constituent with N first, Num scopes over that constituent, and finally Dem takes widest scope. We refer to noun phrase orders that follow this structure as scope-isomorphic. To test for general scope-isomorphic preferences in language users and assess a possible asymmetry between pre- and postnominal modifiers, we tested two linguistic populations with different NP orderings (English and Thai). Learners were exposed to a new language where modifiers were placed on the opposite side of the noun from their native language (i.e., English speakers learned that modifiers in the new language were postnominal and Thai speakers that they were prenominal). Crucially, though, learners were exposed only to single-modifier NPs (e.g., ‘car green’ or ‘car this’) but were not shown how modifiers were ordered relative to one another in multiple modifier phrases. In a test phase, participants were asked how to translate phrases with multiple modifiers into the new language (e.g., ‘this green car’). Speakers of both languages overwhelmingly inferred scope-isomorphic patterns (i.e., they preferred ‘car green this’ over ‘car this green’). We additionally found that Thai participants showed a stronger preference for scope isomorphism, suggesting the possibility that prenominal orders which violate scope isomorphism are particularly dispreferred. We will discuss these results in light of syntactic theory which predicts a pre-/postnominal asymmetry, but will also consider the possible influence of L2 knowledge (specifically Thai speakers’ knowledge of English) on these results, and outline future studies designed to tackle this issue.

The right edge of the word is a known domain for processes like phonological devoicing. This has been argued to be the effect of analogy from higher prosodic domains, rather than an in situ motivated change (Hock 1999, Hualde and Eager 2016). Phonetic word-level phenomena of final lengthening and final devoicing have been found to occur natively word-finally (Lunden 2006, 2017, Nakai et al. 2009) despite claims that they have no natural phonetic pressure originating in this position (Hock 1999). We present the results of artificial language learning studies that seek to answer the question of whether phonetic-level cues to the word-final position can aid in language parsing. If they do, it provides evidence that listeners can make use of word-level phonetic phenomena, which, together with studies that have found them to be present, speaks to their inherent presence at the word level. We find that adult listeners are better able to recognize the words they heard in a speech stream, and better able to reject words that they did not hear, when final lengthening was present at the right edge of the word. Final devoicing was not found to give the same boost to parsing.

Recent work on emerging sign languages provides evidence for how key properties of linguistic systems are created. Here we use laboratory experiments to investigate the contribution of two specific mechanisms—interaction and transmission—to the emergence of a manual communication system in silent gesturers. We show that the combined effects of these mechanisms, rather than either alone, maintain communicative efficiency, and lead to a gradual increase of regularity and systematic structure. The gestures initially produced by participants are unsystematic and resemble pantomime, but come to develop key language-like properties similar to those documented in newly emerging sign systems.

Linguistic animacy reflects a particular construal of biological distinctions encountered in the world, passed through cultural and cognitive filters. This study explores the process by which our construal of animacy becomes encoded in the grammars of human languages. We ran an iterated learning experiment investigating the effect of animacy on language transmission. Participants engaged in a simple artificial language learning task in which they were asked to learn which affix was assigned to each noun in the language. Though initially random, the language each participant produced at test became the language that the subsequent participant in a chain was trained on. Results of the experiment were analysed in terms of learnability, measured through the accuracy of responses, and structure, using an entropy measure. We found that the learnability of languages increased over generations, as expected, but entropy did not decrease. Languages did not become formally simpler over time. Instead, structure emerged through a reorganisation of noun classes around animacy-based categories. The use of semantic animacy distinctions allowed languages to retain morphological complexity while becoming more learnable. Our study shows that grammatical reflexes of animacy distinctions can arise out of learning alone, and that structuring grammar based on animacy can make languages more learnable.

The tendency for languages to use harmonic word order patterns—orders that place heads in a consistent position with respect to modifiers or other dependents—has been noted since the 1960s. As with many other statistical typological tendencies, there has been debate regarding whether harmony reflects properties of human cognition or forces external to it. Recent research using laboratory language learning has shown that children and adults find harmonic patterns easier to learn than nonharmonic patterns (Culbertson & Newport, 2015 ; Culbertson, Smolensky, & Legendre, 2012 ). This supports a link between learning and typological frequency: if harmonic patterns are easier to learn, while nonharmonic patterns are more likely to be targets of change, then, all things equal, harmonic patterns will be more frequent in the world’s languages. However, these previous studies relied on variation in the input as a mechanism for change in the lab; learners were exposed to variable word order, allowing them to shift the frequencies of different orders so that harmonic patterns became more frequent. Here we teach adult and child learners languages that are consistently nonharmonic, with no variation. While adults perfectly maintain these consistently nonharmonic patterns, young child learners innovate novel orders, changing nonharmonic patterns into harmonic ones.

Plural morphology exhibits differing interpretations across languages. For example, in downward entailing contexts in English, the plural receives a one or more (or inclusive) interpretation, whereas in Korean-like languages the plural always receives a more than one (or exclusive) interpretation, regardless of context. Previous experimental work using an artificial language suggests that such differences may follow from structural properties of these languages (Liter, Heffner & Schmitt 2017), namely lack of grammaticalization of the plural/singular distinction. In this paper we adopt Sauerland, Anderssen & Yatsushiro’s (2005) implicated presupposition analysis of the plural (the English plural is semantically unmarked, whereas the Korean plural is semantically marked, carrying a presupposition that the cardinality of its referent is greater than one) in order to test two hypotheses about the interpretation of the plural. Using an artificial language learning paradigm identical to that in Liter, Heffner & Schmitt (2017) with non-grammaticalized number but with a much greater frequency of singular/plural NPs in the input, we test (i) whether semantic markedness of the plural should be linked to the non-grammaticalization of the number paradigm; or (ii) whether semantic markedness follows from insufficient statistical evidence for simplifying the lexical entry for the plural. Our results show that participants continue to assign an exclusive interpretation to plural morphology under the scope of negation, which is compatible with the hypothesis that non-grammaticalized number entails semantic markedness.

Previous research suggests executive function (EF) advantages among bilinguals compared to monolingual peers, and these advantages are generally attributed to experience controlling two linguistic systems. However, the possibility that the relationship between bilingualism and EF might be bidirectional has not been widely considered; while experience with two languages might improve EF, better EF skills might also facilitate language learning. In the current studies, we tested whether adults’ and preschool children’s EF abilities predicted success in learning a novel artificial language. After controlling for working memory and English receptive vocabulary, adults’ artificial language performance was predicted by their inhibitory control ability (Study 1) and children’s performance was predicted by their attentional monitoring and shifting ability (Study 2). These findings provide preliminary evidence suggesting that EF processes may be employed during initial stages of language learning, particularly vocabulary acquisition, and support the possibility of a bidirectional relationship between EF and language acquisition.

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.

The linguist George Kingsley Zipf made a now classic observation about the relationship between a word's length and its frequency; the more frequent a word is, the shorter it tends to be. He claimed that this "Law of Abbreviation" is a universal structural property of language. The Law of Abbreviation has since been documented in a wide range of human languages, and extended to animal communication systems and even computer programming languages. Zipf hypothesised that this universal design feature arises as a result of individuals optimising form-meaning mappings under competing pressures to communicate accurately but also efficiently-his famous Principle of Least Effort. In this study, we use a miniature artificial language learning paradigm to provide direct experimental evidence for this explanatory hypothesis. We show that language users optimise form-meaning mappings only when pressures for accuracy and efficiency both operate during a communicative task, supporting Zipf's conjecture that the Principle of Least Effort can explain this universal feature of word length distributions.

In the present study, we report on an artificial language learning experiment aiming to test the idea that it is easier to learn palatalization before a front vowel than it is to learn depalatalization in the same context. The motivation for the study comes from recent work by Czaplicki (2013), who provides a detailed analysis of palatalization-related effects in Polish, showing that they have no phonological basis. The conclusion he reaches is that ‘phonological naturalness does not play a role in linguistic computation’ Czaplicki (2013:32). It is nevertheless the case that palatalization is cross-linguistically much more common than depalatalization. If naturalness plays no role in computation, the typological asymmetry must arise from elsewhere, for example, from biases in learning difficulty. Our results provide provisory evidence that there is a small but statistically significant advantage for learning palatalization over depalatalization for adult Hungarian speakers.

Previous studies have indicated that dependencies between nonadjacent elements can be acquired by statistical learning when each element predicts only one other element (deterministic dependencies). The present study investigates statistical learning of probabilistic nonadjacent dependencies, in which each element predicts several other elements with a certain probability, as is more common in natural language. Three artificial language learning experiments compared statistical learning of deterministic and probabilistic nonadjacent dependencies. In Experiment 1, participants listened to sequences of three non-words containing either deterministic or probabilistic dependencies between the first and the last non-words. Participants exposed to deterministic dependencies subsequently distinguished correct sequences from sequences that violated the nonadjacent dependencies; participants exposed to probabilistic dependencies did not. However, when visual (Experiment 2) and phonological cues (Experiment 3) were added participants learned both kinds of dependencies, demonstrating statistical learning of probabilistic nonadjacent dependencies when additional cues are present.

The study of language typology has played a critical role in revealing potential constraints on possible linguistic systems. Such constraints, often called “typological universals” have long been used to support a foundational premise of generative linguistics—that languages share a set of underlying commonalities. However, recent research has challenged the idea that typological universals—which (at least on the surface) are often statistical tendencies rather than absolute laws—reflect meaningful biases in the linguistic or cognitive system. In part as a response to these critiques, new behavior methods have been developed to probe the link between recurrent typological patterns and the linguistic (and broader cognitive) system. This article focuses on the novel findings which have resulted from this trend, in particular those which use Artificial Language Learning (ALL) paradigms. This exciting strand of research suggests the viability of experimental methods for investigating constraints on human language, and points to new ways of gaining traction on critical questions in cognitive science.

The artificial language learning paradigm was used to investigate to what extent the use of prosodic features is universally applicable or specifically language driven in learning an unfamiliar language, and how nonnative prosodic patterns can be learned. Listeners of unrelated languages—Dutch (n= 100) and Korean (n= 100)—participated. The words to be learned varied with prosodic cues: no prosody, fundamental frequency (F0) rise in initial and final position, final lengthening, and final lengthening plus F0 rise. Both listener groups performed well above chance level with the final lengthening cue, confirming its crosslinguistic use. As for final F0 rise, however, Dutch listeners did not use it until the second exposure session, whereas Korean listeners used it at initial exposure. Neither group used initial F0 rise. On the basis of these results, F0 and durational cues appear to be universal in the sense that they are used across languages for their universally applicable auditory-perceptual saliency, but how they are used is language specific and constrains the use of available prosodic cues in processing a nonnative language. A discussion on how these findings bear on theories of second language (L2) speech perception and learning is provided.

In an artificial language-learning task, two groups of English and French participants learned one of two language rules: 1) stress the first heavy (CVC) syllable, else the first syllable, or, 2) stress the first light (CV) syllable, else the first syllable. French and English participants were chosen to compare learning outcomes by speakers of different native stress systems, fixed and variable. Participants were trained on the target language by listening to a set of nonsense familiarization words exemplifying the stress rule. This was followed by a forced-choice task to choose the correct version of the words they had just learned. Following the training procedure, participants were tested on novel words with the same stress pattern to which they were familiarized. The result of the novel word testing was that the natural rule with stress on heavy syllables was learned significantly better than the unnatural, stress light syllables, rule. To account for the learnability of both the natural and the unnatural rules, I argue for the interaction of a general cognitive mechanism that facilitates learning in general and a domain-specific language mechanism that can access universal phonological principles to aid in learning a natural language rule.

Prosody has been claimed to have a critical role in the acquisition of grammatical information from speech. The exact mechanisms by which prosodic cues enhance learning are fully unknown. Rules from language often require the extraction of non-adjacent dependencies (e.g., he plays, he sings, he speaks). It has been proposed that pauses enhance learning because they allow computing non-adjacent relations helping word segmentation by removing the need to compute adjacent computations. So far only indirect evidence from behavioral and electrophysiological measures comparing learning effects after exposure to speech with and without pauses support this claim. By recording event-related potentials during the acquisition process of artificial languages with and without pauses between words with embedded non-adjacent rules we provide direct evidence on how the presence of pauses modifies the way speech is processed during learning to enhance segmentation and rule generalization. The electrophysiological results indicate that pauses as short as 25 ms attenuated the N1 component irrespective of whether learning was possible or not. In addition, a P2 enhancement was present only when learning of non-adjacent dependencies was possible. The overall results support the claim that the simple presence of subtle pauses changed the segmentation mechanism used reflected in an exogenously driven N1 component attenuation and improving segmentation at the behavioral level. This effect can be dissociated from the endogenous P2 enhancement that is observed irrespective of the presence of pauses whenever non-adjacent dependencies are learned.

A fundamental question for cognitive science concerns the ways in which languages are shaped by the biases of language learners. Recent research using laboratory language learning paradigms, primarily with adults, has shown that structures or rules that are common in the languages of the world are learned or processed more easily than patterns that are rare or unattested. Here we target child learners , investigating a set of biases for word order learning in the noun phrase studied by Culbertson, Smolensky, and Legendre (2012) in college-age adults. We provide the first evidence that child learners exhibit a preference for typologically common harmonic word order patterns—those which preserve the order of the head with respect to its complements—validating the psychological reality of a principle formalized in many different linguistic theories. We also discuss important differences between child and adult learners in terms of both the strength and content of the biases at play during language learning. In particular, the bias favoring harmonic patterns is markedly stronger in children than adults, and children (unlike adults) acquire adjective ordering more readily than numeral ordering. The results point to the importance of investigating learning biases across development in order to understand how these biases may shape the history and structure of natural languages.

Phonological alternations are attested in many of the world’s languages. In production, these robustly generalize to new words and contexts, suggesting that talkers and listeners of a language have internalized them in some form. However, it is unclear whether listeners’ knowledge of phonological alternations is used during real-time spoken word recognition. The present study asks whether listeners use knowledge of phonological alternations to modulate activation of competitor forms during real-time word recognition. In two experiments, listeners learned an artificial language with phonological alternations. We then used eye-tracking in the visual world paradigm to assess real-time spoken word recognition. We examined fixations to competitors that would be a match to the input because of the learned phonological alternation. Results showed that listeners do use phonological alternations in real time. Given a [t] ~ [d] alternation and an auditory stimulus with a surface [d], listeners fixated the [t]-competitor more than one that could not alternate with [d]. They were even able to generalize this to words that had not been learned in their alternated form. However, not all alternations showed the same pattern; listeners did not use a [d] ~ [z] alternation in the same way. Implications for various models of word recognition are discussed.

Being able to track dependencies between syntactic elements separated by other constituents is crucial for language acquisition and processing (e.g., in subject-noun/verb agreement). Although long assumed to require language-specific machinery, research on statistical learning has suggested that domain-general mechanisms may support the acquisition of non-adjacent dependencies. In this study, we investigated whether individuals with specific language impairment (SLI)—who have problems with long-distance dependencies in language—also have problems with statistical learning of non-adjacent relations. The results confirmed this hypothesis, indicating that statistical learning may subserve the acquisition and processing of long-distance dependencies in natural language.

In recent years, artificial language learning experiments have revealed a rich and complex picture of the abilities of different species and different human age groups to discover simple patterns in sequences. In one influential study, Aslin et al. (1998) show that human infants use transitional probabilities (TP's), and not just co-occurrence frequencies, between adjacent syllables in a monotonous stream of speech to segment it into word-like units

In the present experiment, we used event-related potentials (ERP) to investigate the role of immediate and delayed feedback in an artificial grammar learning task. Two groups of participants were engaged in classifying non-word strings according to an underlying rule system, not known to the participants. Visual feedback was provided after each classification either immediately or with a short delay of one second. Both groups were able to learn the artificial grammar system as indicated by an increase in classification performance. However, the gain in performance was significantly larger for the group receiving immediate feedback as compared to the group receiving delayed feedback. Learning was accompanied by an increase in P300 activity in the ERP for delayed as compared to immediate feedback. Irrespective of feedback delay, both groups exhibited learning related decreases in the feedback-related positivity (FRP) elicited by positive feedback only. The feedback-related negativity (FRN), however, remained constant over the course of learning. These results suggest, first, that delayed feedback is less effective for artificial grammar learning as task requirements are very demanding, and second, that the FRP elicited by positive prediction errors decreases with learning while the FRN to negative prediction errors is elicited in an all-or-none fashion by negative feedback throughout the entire experiment.

Speech perception is a multimodal phenomenon, with what we see impacting what we hear. In this study, we examine how visual information impacts English listeners' segmentation of words from an artificial language containing no cues to word boundaries other than the transitional probabilities (TPs) between syllables. Participants (N=60) were assigned to one of three conditions: Still (still image), Trochaic (image loomed toward the listener at syllable onsets), or Iambic (image loomed toward the listener at syllable offsets). Participants also heard either an easy or difficult variant of the language. Importantly, both languages lacked auditory prosody. Overall performance in a 2AFC test was better in the easy (67%) than difficult language (57%). In addition, across languages, listeners performed best in the Trochaic Condition (67%) and worst in the Iambic Condition (56%). Performance in the Still Condition fell in between (61%). We know English listeners perceive strong syllables as word onsets. Thus, participants likely found the Trochaic Condition easiest because the moving image led them to perceive temporally co-occurring syllables as strong. We are currently testing 6-year-olds (N=25) with these materials. Thus far, children's performance collapsed across conditions is similar to adults (60%). However, visual information may impact children's performance less.

An artificial language learning experiment will be used to study if voice quality can be used to learn tonal systems. Cross‐linguistically, tone, and voice quality can co‐vary in different ways. For instance, Mazatec (Jalapa de Diaz), has three phonation types (modal, breathy, creaky) fully crossed with three level tone levels [Ladefoged et al. (1988)], while Mandarin has creaky phonation in Tone 3 and Tone 4, which are also distinguished from one another and Tone 1 and 2 by f0 contour [Davison (1991); Belotel‐Grenie and Grenie (2004)]. The goal of the study is to investigate if English listeners unfamiliar with tone languages can use phonation‐type contrasts to learn tonal contrasts in artificial tone languages differing in how tone and voice quality co‐vary. There will be a comparison of how learners generalize from training to novel stimuli for artificial languages where voice quality and tone contrasts are correlated and uncorrelated cues.

Successful language acquisition involves generalization, but learners must balance this against the acquisition of lexical constraints. Such learning has been considered problematic for theories of acquisition: if learners generalize abstract patterns to new words, how do they learn lexically-based exceptions? One approach claims that learners use distributional statistics to make inferences about when generalization is appropriate, a hypothesis which has recently received support from Artificial Language Learning experiments with adult learners (Wonnacott, Newport, & Tanenhaus, 2008). Since adult and child language learning may be different (Hudson Kam & Newport, 2005), it is essential to extend these results to child learners. In the current work, four groups of children (6years) were each exposed to one of four semi-artificial languages. The results demonstrate that children are sensitive to linguistic distributions at and above the level of particular lexical items, and that these statistics influence the balance between generalization and lexical conservatism. The data are in line with an approach which models generalization as rational inference and in particular with the predictions of the domain general hierarchical Bayesian model developed in Kemp, Perfors & Tenenbaum, 2006. This suggests that such models have relevance for theories of language acquisition.

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.

Language learning requires mastering multiple tasks, including segmenting speech to identify words, and learning the syntactic role of these words within sentences. A key question in language acquisition research is the extent to which these tasks are sequential or successive, and consequently whether they may be driven by distinct or similar computations. We explored a classic artificial language learning paradigm, where the language structure is defined in terms of non-adjacent dependencies. We show that participants are able to use the same statistical information at the same time to segment continuous speech to both identify words and to generalise over the structure, when the generalisations were over novel speech that the participants had not previously experienced. We suggest that, in the absence of evidence to the contrary, the most economical explanation for the effects is that speech segmentation and grammatical generalisation are dependent on similar statistical processing mechanisms.