Languages exhibit a tremendous amount of variation in how they organise and order morphemes within words; however, regularities are also found. For example, gender and number inflectional morphology tend to appear together within a single affix, and when they appear in two separate affixes, gender marking tends to be placed closer to the stem than number. Formal theories of gender and number have been designed (in part) to explain these tendencies. However, determining whether the abstract representations hypothesised by these theories indeed drive the patterns we find cross-linguistically is difficult, if not impossible, based on the natural language data alone. In this study we use an artificial language learning paradigm to test whether the inferences learners make about the order of gender and number affixes—in the absence of any explicit information in the input—accord with formal theories of how they are represented. We test two different populations, English and Italian speakers, with substantially differ- ent gender systems in their first language. Our results suggest a clear preference for placing gender closest to the noun across these populations, across different types of gender systems, and across prefixing and suffixing morphology. These results expand the range of behavioural evidence for the role of cognitive representations in determining morpheme order.

Syntactic harmony occurs when heads and dependents align within and across different types of phrases in a language. Harmony is a well-known (statistical) typological universal: in most languages, many if not all heads and dependents are consistently ordered (i.e., either head-dependent, or dependent-head). Despite decades of work, from every conceivable theoretical perspective, the origins of syntactic harmony remain opaque. However, recent work using artificial language learning has suggested that harmonic patterns are easier to learn than their non-harmonic counter-parts. Thus at least part of the explanation for this tendency may be linked to learning. Here, we explore whether the mechanism behind the learning bias for syntactic harmony is fundamentally domain-general by instantiating harmony in non-linguistic stimuli. Our findings support the claim that the origins of syntactic harmony lie in a domain-general bias for simplicity acting on linearized, language-specific categories.

Humans use both linear and hierarchical representations in language processing, and the exact role of each has been debated. One domain where hierarchical processing is important is noun phrases. English noun phrases have a fixed order of prenominal modifiers: demonstratives - numerals - adjectives (these two green vases). However, when English speakers learn an artificial language with postnominal modifiers, instead of reproducing this linear order they preserve the distance between each modifier and the noun (vases green two these). This has been explained by a hierarchical homomorphism bias. Here, we investigate whether RNNs exhibit this bias. We pre-train one linear and two hierarchical models on English and expose them to a small artificial language. We then test them on noun phrases from a study with humans and find that only the hierarchical models can exhibit the bias, supporting the idea that homomorphic word order preferences arise from hierarchical, and not linear relations.

Languages partition semantic space into linguistic cate-gories in systematic ways. In this study, we investigatea semantic space which has received sustained attentionin theoretical linguistics: person. Person systems con-vey the roles entities play in the conversational context(i.e., speaker(s), addressee(s), other(s)). Like other lin-guistic category systems (e.g. color and kinship terms),not all ways of partitioning the person space are equallylikely. We use an artificial language learning paradigm totest whether typological frequency correlates with learn-ability of person paradigms. We focus on first personsystems (e.g., ‘I’ and ‘we’ in English), and test the predic-tions of a set of theories which posit a universal set of fea-tures (±exclusive, and ±minimal) to capture this space.Our results provide the first experimental evidence forfeature-based theories of person systems.

Recent studies using artificial language learning have arguedthat the cross-linguistic frequency of harmonic word orderpatterns–in which heads are ordered consistently before or af-ter dependents across syntactic categories–reflects a cognitivebias (Culbertson, Smolensky, & Legendre, 2012; Culbertson& Newport, 2015a). These studies suggest that English speak-ing adults and children favor harmonic orders of nouns anddifferent nominal modifiers (adjectives, numerals). However,because they target English learners, whose native languageis harmonic in the nominal domain (Num-Adj-N), this pref-erence may be based on transfer rather than a universal biasfor harmony. We present new evidence from French-speakingchildren, whose native language is non-harmonic in this do-main (Num-N-Adj). Our results reveal clear effects of nativelanguage transfer, but also evidence that a harmonic pattern isfavored even in this population of learners.

Cross-linguistically, heads tend to be ordered consistently relative to dependents. This tendency is called Cross-Category Harmony. Alternative explanations for harmony include cognitive and non-cognitive processes (e.g., grammaticalization pathways), but evidence disentangling them is still lacking. We report two artificial language learning experiments testing harmony between verb phrases (VP) and adpositional phrases (PP) and between VPs and noun phrases consisting of adjectives and nouns (NP). These two cases are critically different: typological evidence for the former is strong but there is no typological evidence for the latter. Our results parallel the typology; we find a strong preference for harmonic orders between VP and PP regardless whether the participants’ native language has harmonic order (English speakers) or mixed orders (Chinese speakers), but no preference for harmonic order between VP and NP. This suggests that a cognitive bias for harmony may play a role in shaping typology.

Numeral classifiers are a noun categorization device found in many East and Southeast Asian languages. Their syntactic status is debated: some theories treat them as forming a constituent with the noun, others with the numeral. Typological data on how classifiers, numerals, and nouns are ordered largely support the classifier-with-numeral hypothesis: orders in which the noun intervenes between the numeral and the classifier are unattested. However, typological evidence is problematic in this case, because the distribution of classifiers is highly geographically constrained, and ordering tendencies may reflect language contact. In this study, we look for evidence of the syntactic status of classifiers using artificial language learning experiments. We test whether learners’ preference among patterns are predicted by one of these two accounts. Results suggest that, if anything, learners in fact prefer orders that group classifiers with the numeral.

Animacy is prevalent in as a semantic basis for noun classification systems (i.e., grammatical gender, noun classes and classifiers), but colour is completely absent, despite its visual salience. The absence of colour in such systems is sometimes argued to suggest domain-specific constraints on what is grammatically encodable. Here, we investigate whether this tendency could instead be explained by the superior predictive power of animacy (i.e., the degree to which it predicts other features) compared to colour. In a series of experiments, we find that animacy-based noun classes are learned better than colour-based ones. However, when participants are encouraged, by manipulating predictive power, to sort images based on colour, they are worse at learning animacy-based noun classes. The results suggest the animacy bias in grammar may have its roots in domain-general categorisation principles. They further serve as evidence for the role of cognitive biases in constraining cross-linguistic variation.

Typological data shows a tendency for languages to exhibit harmonic (i.e. consistent) ordering between heads and dependents. However, some categories seem to contradict this tendency. Here we investigate one such case, the order of the noun with respect to two dependents—adjectives, which tend to follow the noun and genitives which precede. We report two silent gesture experiments examining (i) whether there are cognitive biases favouring postnominal adjective and prenominal genitive order in a single trial judgement task, and (ii) if those preferences continue to influence order when participants learn a complete word order system. Our results shed light on how biases for individual categories of elements interact with biases that affect the wider linguistic system. While participants strongly prefer postnominal adjectives and prenominal genitives when these are judged in isolation, when they learn a system of ordering, these biases are obscured and (at least in some cases) harmony emerges.