The prevalence of redundancy in the world languages has long puzzled language researchers. It is especially surprising in light of the growing evidence on speakers' tendency to avoid redundant ...elements in production (omitting or reducing more predictable elements). Here, we propose that redundancy can be functional for learning. In particular, we argue that redundant cues can facilitate learning, even when they make the language system more complicated. This prediction is further motivated by the Linguistic Niche Hypothesis (Lupyan & Dale, 2010), which suggests that morphological complexity can arise due to the advantage redundancy might confer for child learners. We test these hypotheses in an artificial language learning study with children and adults, where either word order alone or both word order and case marking serve as cues for thematic assignment in a novel construction. We predict, and find, that children learning the redundant language learn to produce it, and show better comprehension of the novel thematic assignment than children learning the non-redundant language, despite having to learn an additional morpheme. Children in both conditions were similarly accurate in producing the novel word order, suggesting redundancy might have a differential effect on comprehension and production. Adults did not show better learning in the redundant condition, most likely because they were at ceiling in both conditions. We discuss implications for theories of language learning and language change.
It is often assumed that cross-linguistically more prevalent distinctions are easier to learn (Typological Prevalence Hypothesis; TPH). Prior work supports this idea in phonology, morphology and ...syntax but has not addressed semantics. Using Artificial Language Learning experiments with adults, we test predictions made by the TPH about the relative learnability of semantic distinctions in the domain of evidentiality, i.e., the linguistic encoding of information source. As the TPH predicted, when exposed to miniature evidential morphological systems, adult speakers of English whose language does not encode evidentiality grammatically learned the typologically most prevalent system (marking indirect, reportative information) better compared to less-attested systems (Experiments 1–2). Similar patterns were observed when non-linguistic symbols were used to encode evidential distinctions (Experiment 3). Our data support the conjecture that some semantic distinctions are marked preferentially and acquired more easily compared to others in both language and other symbolic systems.
Language learning involves exposure to inconsistent systems - that is, systems where multiple patterns or methods exist to mark some meaning. Inconsistent systems often change to be more regular over ...time - they become systematized. However, some recent studies have reported that learners tend to reproduce inconsistency in the input, leading to models in which the language learning mechanism is basically preservatory. We ran an artificial language learning experiment using a novel paradigm to extend our understanding of systematizing versus preservatory mechanisms in language learning. Participants were taught two number marking systems, either completely consistently (the probability P of the system is 1.00) or inconsistently (with P = 0.875 for one system and P = 0.125 for the other, and so on for P = 0.75 and P = 0.625). One marking system was a plural-marking system. The other was a typologically rare singulative-marking system. When generalizing to novel items, participants produced more regular output patterns overall for more consistent input conditions than for less consistent ones, and more for the plural-marking conditions than for the singulative-marking conditions. For the singulative-marking conditions, the inter-participant variation was much greater than for the plural-marking ones; some individuals systematized towards the more familiar pattern, some systematized towards the less familiar pattern and some were not significantly different from probability-matching. We analyze the variation in relation to current statistical learning models, showing that preservatory learning models, as well as all models with a single free parameter, fail to capture our results. We show how a model with two free parameters in which individuals can vary in their propensity to systematize in any given situation is more successful. We also discuss implications for the theory of language change.
We examine how learning a phonological rule in an artificial language interacts with morphological and lexical learning. We exposed adult participants to an artificial language in which noun plurals ...were marked by one of two prefix forms (ba- or ni-), one of which also triggered a velar palatalization rule (e.g., singular kimu, plural ni-chimu). In some conditions, the rule additionally created homophony. We also manipulated the relative frequency of the two prefix variants. The results showed that participants shifted away from using the rule-triggering prefix (ni-), but only when it was already the less frequent prefix. We attribute this effect to a paradigm uniformity bias leading participants to avoid phonological alternations (particularly in the stem). When the rule created homophony between lexical items, participants were less able to learn the rule, but it did not affect their choice of prefix. We attribute this effect to homophony avoidance interfering with participants' ability to extract the phonological generalization.
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.
•A novel technique showing how priming and interaction led to linguistic regularity.•Participants learnt artificial languages, then interacted using those languages.•Structural priming occurred in ...two different grammatical constructions.•Interaction resulted in the reduction of unpredictable linguistic variation.
We present a novel experimental technique using artificial language learning to investigate the relationship between structural priming during communicative interaction, and linguistic regularity. We use unpredictable variation as a test-case, because it is a well-established paradigm to study learners’ biases during acquisition, transmission and interaction. We trained participants on artificial languages exhibiting unpredictable variation in word order, and subsequently had them communicate using these artificial languages. We found evidence for structural priming in two different grammatical constructions and across human-human and human-computer interaction. Priming occurred regardless of behavioral convergence: communication led to shared word order use only in human-human interaction, but priming was observed in all conditions. Furthermore, interaction resulted in the reduction of unpredictable variation in all conditions, suggesting a role for communicative interaction in eliminating unpredictable variation. Regularisation was strongest in human-human interaction and in a condition where participants believed they were interacting with a human but were in fact interacting with a computer. We suggest that participants recognize the counter-functional nature of unpredictable variation and thus act to eliminate this variability during communication. Furthermore, reciprocal priming occurring in human-human interaction drove some pairs of participants to converge on maximally regular, highly predictable linguistic systems. Our method offers potential benefits to both the artificial language learning and the structural priming fields, and provides a useful tool to investigate communicative processes that lead to language change and ultimately language design.
•Children privilege phonology over semantics in noun class learning.•We use artificial language experiments to investigate potential mechanisms.•When phonological and semantic cues conflict, adults ...use the more salient cue.•However, less salient cues are preferred when they are available earlier.•Child learners may thus privilege phonology because it is accessible before meaning.
Learning noun classification systems, like gender, involves inferring a language-particular set of (often probabilistic) cues to class membership. Previous work has shown that learners rely disproportionately on phonological cues (e.g., Gagliardi & Lidz, 2014; Karmiloff-Smith, 1981). Surprisingly, this occurs even when competing semantic cues are more reliable predictors of class. We investigate two possible explanations for this: first, that phonological cues are more salient to learners than semantic cues, and second that phonological cues are generally available earlier than semantic cues. We show that adult learners’ treatment of conflicting cues to noun class in a miniature artificial language depends on both cue saliency and early availability. Importantly, learners prioritize earlier-available cues even when they are less salient than competitor cues. Our findings suggest a possible mechanism for children’s over-reliance on phonology: children start building their classifications systems very early, when phonological information is available, but word meanings are not.
Experimental work in the field of language evolution has shown that novel signal systems become more structured over time. In a recent paper, Kirby, Tamariz, Cornish, and Smith (2015) argued that ...compositional languages can emerge only when languages are transmitted across multiple generations. In the current paper, we show that compositional languages can emerge in a closed community within a single generation. We conducted a communication experiment in which we tested the emergence of linguistic structure in different micro-societies of four participants, who interacted in alternating dyads using an artificial language to refer to novel meanings. Importantly, the communication included two real-world aspects of language acquisition and use, which introduce compressibility pressures: (a) multiple interaction partners and (b) an expanding meaning space. Our results show that languages become significantly more structured over time, with participants converging on shared, stable, and compositional lexicons. These findings indicate that new learners are not necessary for the formation of linguistic structure within a community, and have implications for related fields such as developing sign languages and creoles.
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.
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.
•Child and adult learners are biased in favor of harmonic word order patterns.•This bias holds even when learners' native language is non-harmonic.•The typological prevalence of harmony may thus be explained by biases in learning.
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