Multimodal Transfer of Repetition Patterns in Artificial Grammar Learning.

Multimodal Transfer of Repetition Patterns in Artificial Grammar Learning Sara Finley (sfinley@bcs.rochester.edu) Department of Brain and Cognitive Sciences, Meliora Hall, University of Rochester Rochester, NY 146270 USA Morten H. Christiansen (christiansen@cornell.edu) Department of Psychology, Uris Hall, Cornell University Ithaca, NY 14853 USA Abstract transmission, give rise to recurring cross-linguistic patterns, rather than absolute language universals (Evans & Levinson, 2009). Through cultural evolution, language has been shaped to fit learners, and this helps explain the impressive language acquisition abilities of children (Chater & Christiansen, 2010). However, empirically uncovering the role of domain- general and domain-specific learning mechanisms in language has proven rather difficult because language development is intertwined with the development of other cognitive functions. A potential way to untangle the contribution of domain-general and domain-specific processes is to explore learning in a controlled environment. Artificial grammar learning paradigms offer a mechanism to explore learning of both linguistic and non-linguistic stimuli in isolation, allowing the researcher to compare domain- general and domain-specific effects of learning in a controlled environment. Under the guise of statistical learning, this experimental paradigm has been used to explore different aspects of learning, such as word segmentation (Saffran, Aslin, & Newport, 1996) and non- linguistic patterns (Kirkham, Slemmer, & Johnson, 2002). In this paper, we test the hypothesis that domain-general learning mechanisms make it possible to generalize a pattern from a linguistic domain to a non-linguistic analogue, and vice versa. If learners are able to learn novel linguistic patterns in a way that is flexible beyond language- specific learning, they should be able to transfer that pattern to a non-linguistic analogue. One difficulty in assessing transfer from linguistic phenomena to non-linguistic analogues (and vice versa) is that some linguistic patterns and processes have no straightforward non-linguistic analogue. A non-linguistic version of complex syntactic phenomena, such as non- adjacent dependencies in subject-verb agreement, may be difficult to map onto non-linguistic, domain-general cognition. For example, in English, the subject of a sentence must agree in number with the verb of the sentence, even if the subject and the verb are not adjacent in the sentence (e.g., The boys in the corner like bananas). Such agreement patterns are not easy to translate into alternative domains (though see Onnis, Christiansen, Chater, & Gomez, 2003 for a study of nonadjacency learning using visual nonsense shapes). Even in less ‘abstract’ domains of language such as phonetics and phonology, it is difficult to find non-linguistic analogues for patterns because phonological patterns would Extending learned patterns to previously unseen ones is a key hallmark of complex cognition. This paper presents evidence that learners are able to generalize learned patterns to novel stimuli with very different surface properties within and across modalities. Using a statistical learning paradigm, adult learners were exposed to a repetition (reduplication) pattern in which the first element of a three-element sequence repeated (e.g., ABAAB). The pattern was presented as either spoken repetition (e.g., bago, babago) or a non-linguistic visual analogue (i.e., repetition of non-nameable shapes). Learners showed significant transfer from a non-linguistic repetition pattern to a linguistic reduplication pattern, and vice versa. However, we found a small bias towards linguistic reduplication, as responses to linguistic patterns were numerically higher. This suggests that while learners are able to extend learned patterns to novel patterns in other domains, factors such as familiarity and naturalness may privilege linguistic patterns over non-linguistic analogues. Keywords: statistical learning, reduplication, domain-general learning mechanisms, generalization. Domain-generality in Language One of the most hotly debated topics in the cognitive science of language is whether the mechanisms involved in language acquisition and processing are primarily specific to the domain of language, or whether they may be domain- general and play a role in other aspects of cognition. Domain-specific learning mechanisms have typically been championed by generative linguists, who see language as a highly abstract communicative system governed by complex rules. The complexity and abstractness of these rules have led many to believe that language is one of the key components that separate humans from other species (e.g., Pinker & Jackendoff, 2009). Such language-specific mechanisms provide a possible account for the complexity of language, language universals, as well as the relative ease with which children can learn complicated language systems without explicit instruction. An alternative account of the complexities of language development focuses on the potential role of domain-general mechanisms in the acquisition and processing of language. This perspective suggests that the regularities found across languages derive from processes of cultural evolution piggy- backing on top of general cognitive mechanisms (Christiansen & Chater, 2008). Constraints on these domain-general mechanisms, amplified by cultural