There are times when a curiously odd relic of language presents us with a thread, which when pulled, reveals deep and general facts about human language. This paper unspools such a case. Prior to 1930, English speakers uniformly preferred male-before-female word order in conjoined nouns such asuncles and aunts; nephews and nieces; men and women. Since then, at least a half dozen items have systematically reversed their preferred order (e.g.,aunts and uncles, nieces and nephews) while others have not (men and (...) women). We review evidence that the unusual reversals began withmother and dad(dy)and spread to semantically and morphologically related binomials over a period of decades. The present work proposes that three aspects ofcognitive accessibilitycombine to quantify the probability of A&B order: (1) the relative accessibility of the A&B terms individually, (2) competition from B&A order, and critically, (3) cluster strength (i.e., similarity to related A'&B' cases). The emergent cluster of female-first binomials highlights the influence of semantic neighborhoods in memory retrieval. We suggest that cognitive accessibility can be used to predict the word order of both familiar and novel binomials generally, as well as the diachronic change focused on here. (shrink)

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. (shrink)

Polysemy, understood as instances of a single linguistic expression having multiple related senses, is not a homogenous phenomenon. There are regular (apparently, rule‐based) cases and irregular (resemblance‐based) cases, which have different processing profiles. Although a primary source of polysemy is pragmatic inference, at least some cases become conventionalised and linguistically encoded. Three main issues are discussed: (a) the key differences between regular and irregular cases and the role, if any, of a “core meaning”; (b) the distinction between pragmatic polysemy and (...) semantic polysemy; and (c) the role of syntactic meaning in both generating and constraining polysemy. (shrink)

We trained a computational model (the Chunk-Based Learner; CBL) on a longitudinal corpus of child–caregiver interactions in English to test whether one proposed statistical learning mechanism—backward transitional probability—is able to predict children's speech productions with stable accuracy throughout the first few years of development. We predicted that the model less accurately reconstructs children's speech productions as they grow older because children gradually begin to generate speech using abstracted forms rather than specific “chunks” from their speech environment. To test this idea, (...) we trained the model on both recently encountered and cumulative speech input from a longitudinal child language corpus. We then assessed whether the model could accurately reconstruct children's speech. Controlling for utterance length and the presence of duplicate chunks, we found no evidence that the CBL becomes less accurate in its ability to reconstruct children's speech with age. (shrink)

In 2006, Perruchet and Pacton (2006) asked whether implicit learning and statistical learning represent two approaches to the same phenomenon. This article represents an important follow‐up to their seminal review article. As in the previous paper, the focus is on the formation of elementary cognitive units. Both approaches favor different explanations on what these units consist of and how they are formed. Perruchet weighs up the evidence for different explanations and concludes with a helpful agenda for future research.

In this review article, Christiansen provides a historical perspective on the two research traditions, implicit learning and statistical learning, thus nicely setting the scene for this special issue of Topics in Cognitive Science. In this “tale of two literatures”, he first traces the history of both literatures before sketching a framework that provides a basis for understanding implicit learning and statistical learning as a unified phenomenon.

Corpus surveys have shown that the exact forms with which idioms are realized are subject to variation. We report a rating experiment showing that such alternative realizations have varying degrees of acceptability. Idiom variation challenges processing theories associating idioms with fixed multi-word form units, fixed configurations of words, or fixed superlemmas, as they do not explain how it can be that speakers produce variant forms that listeners can still make sense of. A computational model simulating comprehension with naive discriminative learning (...) is introduced that provides an explanation for the different degrees of acceptability of several idiom variant types. Implications for multi-word units in general are discussed. (shrink)

Whereas a growing bulk of work has demonstrated that both adults and children are sensitive to frequently occurring word sequences, little is known about the potential role of meaning in the processing of such multiword chunks. Here, we take a first step toward assessing the contribution of meaningfulness in the processing of multiword sequences, using items that varied in chunk meaningfulness. In a phrasal-decision study, we compared reaction times for triads of three-word sequences, corresponding to idiomatic expressions, compositional phrases, and (...) phrasal fragments, while controlling for phrase and substring frequencies. Chunk meaningfulness, as assessed by a separate subjective rating study, was found to speed up decision times for all three types of strings: The more meaningful a multiword sequence was judged to be, the faster it was processed, independently of whether it was idiomatic, compositional in nature, or a phrasal fragment. These results highlight the importance of taking meaning into account when considering the processing of multiword chunks, consistent with predictions of construction-based approaches to language. (shrink)

Framed in psychological terms, the basic question of linguistic theory is what is stored in memory, and in what form. Traditionally, what is stored is divided into grammar and lexicon, where grammar contains the rules and the lexicon is an unstructured list of exceptions. We develop an alternative view in which rules of grammar are simply lexical items that contain variables, and in which rules have two functions. In their generative function, they are used to build novel structures, just as (...) in traditional generative linguistics. In their relational function, they capture generalizations over stored items in the lexicon, a role not seriously explored in traditional linguistic theory. The result is a highly structured lexicon with rich patterns among stored items. We further explore the possibility that this sort of structuring is not specific to language, but appears in other cognitive domains as well, such as the structure of physical objects, of music, and of geographical and social knowledge. The differences among cognitive domains do not lie in this overall texture, but in the materials over which stored relations are defined. The challenge is to develop theories of representation in these other domains comparable to that for language. (shrink)

Prior research has shown that various types of conventional multiword chunks are processed faster than matched novel strings, but it is unclear whether this processing advantage extends to variant multiword chunks that are less formulaic. To determine whether the processing advantage of multiword chunks accommodates variations in the canonical phrasal template, we examined the robustness of the processing advantage (i.e., predictability) of binomial phrases with non‐canonical conjunctions (e.g.,salt and also pepper; salt as well as pepper). Results from the cloze study (...) (Experiment 1) showed that there was a high tendency of producing the canonical conjunct (pepper), even in the binomials that contained non‐formulaic conjunctions. Consistent with these findings, results from two eye tracking studies (Experiments 2a and 2b) showed that canonical conjuncts were read faster than novel conjuncts that were matched on word length (e.g.,paprika), even in the binomials with variant conjunctions. This robust online processing advantage was replicated in a self‐paced reading study that compared all three conjunction types (Experiment 3). Taken together, these findings show that binomials with variant function words also receive facilitated processing relative to matched novel strings, even though both types of strings are neither conventional nor relatively frequent. Exploratory analyses revealed that this processing speed advantage was driven by the lexical–semantic association between the canonical conjuncts (salt–pepper), rather than lexical and phrasal frequency. Overall, these results highlight flexibility in the processing of multiword chunks that current models of multiword storage and processing must take into account. (shrink)