Cognitive Science, Volume 46, Issue 8, August 2022.

Cognitive Science, Volume 46, Issue 3, March 2022.

One approach to understanding how the human cognitive system stores and operates with quantifiers such as “some,” “many,” and “all” is to investigate their interaction with the cognitive mechanisms for estimating and comparing quantities from perceptual input (i.e., nonsymbolic quantities). While a potential link between quantifier processing and nonsymbolic quantity processing has been considered in the past, it has never been discussed extensively. Simultaneously, there is a long line of research within the field of numerical cognition on the relationship between (...) processing exact number symbols (such as “3” or “three”) and nonsymbolic quantity. This accumulated knowledge can potentially be harvested for research on quantifiers since quantifiers and number symbols are two different ways of referring to quantity information symbolically. The goal of the present review is to survey the research on the relationship between quantifiers and nonsymbolic quantity processing mechanisms and provide a set of research directions and specific questions for the investigation of quantifier processing. (shrink)

The idea that ambiguity can be productive in data science remains controversial. Efforts to make scientific publications and data intelligible to computers generally assume that accommodating multiple meanings for words, known as polysemy, undermines reasoning and communication. This assumption has nonetheless been contested by historians, philosophers, and social scientists, who have applied qualitative research methods to demonstrate the generative and strategic value of polysemy. Recent quantitative results from linguistics have also shown how polysemy can actually improve the efficiency of human (...) communication. I present a new conceptual typology based on a synthesis of prior research about the aims, norms, and circumstances under which polysemy arises and is evaluated. The typology supports a contextual pluralist view of polysemy’s value for scientific research practices: polysemy does both substantial positive and negative work in science, but its utility is context-sensitive in ways that are often overlooked by the norms people have formulated to regulate its use, including prior scholars researching polysemy. I also propose that historical patterns in the use of partial synonyms, i.e. terms with overlapping meanings, provide an especially promising phenomenon for integrative research addressing these issues. (shrink)

Cognitive Science, Volume 46, Issue 5, May 2022.

Cognitive Science, Volume 46, Issue 6, June 2022.

Words are processed more easily when they have canonical phonotactic shapes, i.e., shapes that are frequent both in the lexicon and in usage. We explore whether this cognitively grounded constraint or preference implies testable predictions about the implementation of sound change. Specifically, we hypothesise that words with canonical shapes favour, or ‘select for’, sound changes that produce words with the same shapes. To test this, we investigate a Middle English sound change known as Open Syllable Lengthening. OSL lengthened vowels in (...) disyllables such as ME /ma.kə/ make, but more or less only when they became monosyllabic and when their vowels were non-high. We predict that word shapes produced by this implementation pattern should correspond to the shapes that were most common among morphologically simple monosyllables and disyllables at the time when OSL occurred. We test this prediction against Early Middle English corpus data. Our results largely confirm our prediction: monosyllables produced by OSL indeed conformed to the shapes that were most frequent among already existing monosyllables. At the same time, the failure of OSL to affect disyllables prevented them from assuming shapes that were far more typical of morphologically complex word forms than of simple ones. This suggests that the actuation and implementation of sound changes may be even more sensitive to lexical probabilities than hitherto suspected. Also, it demonstrates how diachronic data can be used to test hypotheses about constraints on word recognition and processing. (shrink)

Procedural metacognition is the set of affect-based mechanisms allowing agents to regulate cognitive actions like perceptual discrimination, memory retrieval or problem solving. This article proposes that procedural metacognition has had a major role in the evolution of communication. A plausible hypothesis is that, under pressure for maximizing signalling efficiency, the metacognitive abilities used by nonhumans to regulate their perception and their memory have been re-used to regulate their communication. On this view, detecting one’s production errors in signalling, or solving species-specific (...) trade-offs between informativeness, processing effort, clarity, or urgency depend on a form of procedural metacognition, called “metacommunication”. How does this view relate to Gricean theories of human communication? A parallel between procedural trade-offs and conversational maxims is discussed for its evolutionary implications. Rather than accepting radically discontinuist interpretations, in which mindreading operates a full reorganization of pragmatics, it is proposed that procedural forms of regulation are entrenched in all forms of human communication. According to contextual demands, humans adopt and monitor more or less demanding informational goals, such as factual updating, clarifying, explaining, proving, and reaching consensus in collective matters. Under time pressure, only part of these goals require adopting others’ viewpoint. Efficiency in collective decision-making, in particular, might have been considerably raised by an ability to interpret others’ intentions and motivations. (shrink)

Silent gestures consist of complex multi‐articulatory movements but are now primarily studied through categorical coding of the referential gesture content. The relation of categorical linguistic content with continuous kinematics is therefore poorly understood. Here, we reanalyzed the video data from a gestural evolution experiment (Motamedi, Schouwstra, Smith, Culbertson, & Kirby, 2019), which showed increases in the systematicity of gesture content over time. We applied computer vision techniques to quantify the kinematics of the original data. Our kinematic analyses demonstrated that gestures (...) become more efficient and less complex in their kinematics over generations of learners. We further detect the systematicity of gesture form on the level of thegesture kinematic interrelations, which directly scales with the systematicity obtained on semantic coding of the gestures. Thus, from continuous kinematics alone, we can tap into linguistic aspects that were previously only approachable through categorical coding of meaning. Finally, going beyond issues of systematicity, we show how unique gesture kinematic dialects emerged over generations as isolated chains of participants gradually diverged over iterations from other chains. We, thereby, conclude that gestures can come to embody the linguistic system at the level of interrelationships between communicative tokens, which should calibrate our theories about form and linguistic content. (shrink)

In recent years, dependency grammars have established themselves as valuable tools in theoretical and computational linguistics. To many linguists, dependency grammars and the more standard constituency-based formalisms are notational variants. We argue that, beyond considerations of formal equivalence, cognition may also serve as a background for a genuine comparison between these different views of syntax. In this paper, we review and evaluate some of the most common arguments and evidence employed to advocate for the cognitive or neural reality of dependency (...) grammars in linguistics, psycholinguistics, or neurolinguistics. We then raise the possibility that the abilities to represent and track, alternatively or in parallel, constituency and dependency structures co-exist in human cognition and are constitutive of syntactic competence. (shrink)

Cognitive Science, Volume 46, Issue 2, February 2022.

The amount of information conveyed by linguistic conventions depends on their precision, yet the codes that humans and other animals use to communicate are quite ambiguous: they may map several vague meanings to the same symbol. How does semantic precision evolve, and what are the constraints that limit it? We address this question using a multiplayer gaming app, where individuals communicate with one another in a scaled-up referential game. Here, the goal is for a sender to use black and white (...) symbols to communicate colors. We expected that the players’ mappings between symbols and colors would grow more specific over time, through a selection process whereby precise mappings are preferentially copied. We found that players become increasingly more precise in their use of symbols over the course of their interactions. This trend did not, however, result from selective copying of precise mappings. We explore the implications of this result for the study of lexical ambiguity, Zipf's Law of Meaning, and disagreements over semantic conventions. (shrink)

Iconicity, the resemblance between the form of a word and its meaning, has effects on behavior in both communicative symbol development and language learning experiments. These results have invited speculation about iconicity being a key feature of the origins of language, yet the presence of iconicity in natural languages seems limited. In a diachronic study of language change, we investigated the extent to which iconicity is a stable property of vocabulary, alongside previously investigated psycholinguistic predictors of change. Analyzing 784 English (...) words with data on their historical forms, we found that stable words are higher in iconicity, longer in length, and earlier acquired during development, but that the role of frequency and grammatical category may be less important than previously suggested. Iconicity is revealed as a feature of ultra-conserved words and potentially also as a property of vocabulary early in the history of language origins. (shrink)

Over the history of research on sign languages, much scholarship has highlighted the pervasive presence of signs whose forms relate to their meaning in a non-arbitrary way. The presence of these forms suggests that sign language vocabularies are shaped, at least in part, by a pressure toward maintaining a link between form and meaning in wordforms. We use a vector space approach to test the ways this pressure might shape sign language vocabularies, examining how non-arbitrary forms are distributed within the (...) lexicons of two unrelated sign languages. Vector space models situate the representations of words in a multi-dimensional space where the distance between words indexes their relatedness in meaning. Using phonological information from the vocabularies of American Sign Language and British Sign Language, we tested whether increased similarity between the semantic representations of signs corresponds to increased phonological similarity. The results of the computational analysis showed a significant positive relationship between phonological form and semantic meaning for both sign languages, which was strongest when the sign language lexicons were organized into clusters of semantically related signs. The analysis also revealed variation in the strength of patterns across the form-meaning relationships seen between phonological parameters within each sign language, as well as between the two languages. This shows that while the connection between form and meaning is not entirely language specific, there are cross-linguistic differences in how these mappings are realized for signs in each language, suggesting that arbitrariness as well as cognitive or cultural influences may play a role in how these patterns are realized. The results of this analysis not only contribute to our understanding of the distribution of non-arbitrariness in sign language lexicons, but also demonstrate a new way that computational modeling can be harnessed in lexicon-wide investigations of sign languages. (shrink)

Cross-linguistic studies focus on inverse correlations (trade-offs) between linguistic variables that reflect different cues to linguistic meanings. For example, if a language has no case marking, it is likely to rely on word order as a cue for identification of grammatical roles. Such inverse correlations are interpreted as manifestations of language users’ tendency to use language efficiently. The present study argues that this interpretation is problematic. Linguistic variables, such as the presence of case, or flexibility of word order, are aggregate (...) properties, which do not represent the use of linguistic cues in context directly. Still, such variables can be useful for circumscribing the potential role of communicative efficiency in language evolution, if we move from cross-linguistic trade-offs to multivariate causal networks. This idea is illustrated by a case study of linguistic variables related to four types of Subject and Object cues: case marking, rigid word order of Subject and Object, tight semantics and verb-medial order. The variables are obtained from online language corpora in thirty languages, annotated with the Universal Dependencies. The causal model suggests that the relationships between the variables can be explained predominantly by sociolinguistic factors, leaving little space for a potential impact of efficient linguistic behavior. (shrink)

The transformers that drive chatbots and other AI systems constitute large language models (LLMs). These are currently the focus of a lively discussion in both the scientific literature and the popular media. This discussion ranges from hyperbolic claims that attribute general intelligence and sentience to LLMs, to the skeptical view that these devices are no more than “stochastic parrots”. I present an overview of some of the weak arguments that have been presented against LLMs, and I consider several of the (...) more compelling criticisms of these devices. The former significantly underestimate the capacity of transformers to achieve subtle inductive inferences required for high levels of performance on complex, cognitively significant tasks. In some instances, these arguments misconstrue the nature of deep learning. The latter criticisms identify significant limitations in the way in which transformers learn and represent patterns in data. They also point out important differences between the procedures through which deep neural networks and humans acquire knowledge of natural language. It is necessary to look carefully at both sets of arguments in order to achieve a balanced assessment of the potential and the limitations of LLMs. (shrink)

Word co‐occurrence patterns in language corpora contain a surprising amount of conceptual knowledge. Large language models (LLMs), trained to predict words in context, leverage these patterns to achieve impressive performance on diverse semantic tasks requiring world knowledge. An important but understudied question about LLMs’ semantic abilities is whether they acquire generalized knowledge of common events. Here, we test whether five pretrained LLMs (from 2018's BERT to 2023's MPT) assign a higher likelihood to plausible descriptions of agent−patient interactions than to minimally (...) different implausible versions of the same event. Using three curated sets of minimal sentence pairs (total n = 1215), we found that pretrained LLMs possess substantial event knowledge, outperforming other distributional language models. In particular, they almost always assign a higher likelihood to possible versus impossible events (The teacher bought the laptop vs. The laptop bought the teacher). However, LLMs show less consistent preferences for likely versus unlikely events (The nanny tutored the boy vs. The boy tutored the nanny). In follow‐up analyses, we show that (i) LLM scores are driven by both plausibility and surface‐level sentence features, (ii) LLM scores generalize well across syntactic variants (active vs. passive constructions) but less well across semantic variants (synonymous sentences), (iii) some LLM errors mirror human judgment ambiguity, and (iv) sentence plausibility serves as an organizing dimension in internal LLM representations. Overall, our results show that important aspects of event knowledge naturally emerge from distributional linguistic patterns, but also highlight a gap between representations of possible/impossible and likely/unlikely events. (shrink)

Cognitive Science, Volume 45, Issue 11, November 2021.

The language we use over the course of conversation changes as we establish common ground and learn what our partner finds meaningful. Here we draw upon recent advances in natural language processing to provide a finer‐grained characterization of the dynamics of this learning process. We release an open corpus (>15,000 utterances) of extended dyadic interactions in a classic repeated reference game task where pairs of participants had to coordinate on how to refer to initially difficult‐to‐describe tangram stimuli. We find that (...) different pairs discover a wide variety of idiosyncratic but efficient and stable solutions to the problem of reference. Furthermore, these conventions are shaped by the communicative context: words that are more discriminative in the initial context (i.e., that are used for one target more than others) are more likely to persist through the final repetition. Finally, we find systematic structure in how a speaker's referring expressions become more efficient over time: Syntactic units drop out in clusters following positive feedback from the listener, eventually leaving short labels containing open‐class parts of speech. These findings provide a higher resolution look at the quantitative dynamics of ad hoc convention formation and support further development of computational models of learning in communication. (shrink)

Structurally, cognitive and biological evolution are highly similar. Random variation and constant but blind selection drive evolution within biology as well as within cognition. However, evolution of cognitive programs, and in particular of grammar systems, is not a subclass of biological evolution but a domain of its own. The abstract evolutionary principles, however, are akin in cognitive and biological evolution. In other words, insights gained in the biological domain can be cautiously applied to the cognitive domain. This paper claims that (...) the cognitively encapsulated, i.e. consciously inaccessible, aspects of grammars as cognitively represented systems, that is, the procedural and structural parts of grammars, are subject to, and results of, Darwinian evolution, applying to a domain-specific cognitive program. Other, consciously accessible aspects of language do not fall under Darwinian evolutionary principles, but are mostly instances of social changes. (shrink)

We investigate the order in which speakers produce the proper names of couples they know personally in English and Japanese, two languages with markedly different constituent word orders. Results demonstrate that speakers of both languages tend to produce the name of the person they feel closer to before the name of the other member of the couple (N = 180). In this way, speakers’ unique personal histories give rise to a remarkably systematic linguistic generalization in both English and Japanese. Insofar (...) as closeness serves as an index of cognitive accessibility, the current work demonstrates that systematicity emerges from a domain-general property of memory. (shrink)

A key component of research on human sentence processing is to characterize the processing difficulty associated with the comprehension of words in context. Models that explain and predict this difficulty can be broadly divided into two kinds, expectation‐based and memory‐based. In this work, we present a new model of incremental sentence processing difficulty that unifies and extends key features of both kinds of models. Our model, lossy‐context surprisal, holds that the processing difficulty at a word in context is proportional to (...) the surprisal of the word given a lossy memory representation of the context—that is, a memory representation that does not contain complete information about previous words. We show that this model provides an intuitive explanation for an outstanding puzzle involving interactions of memory and expectations: language‐dependent structural forgetting, where the effects of memory on sentence processing appear to be moderated by language statistics. Furthermore, we demonstrate that dependency locality effects, a signature prediction of memory‐based theories, can be derived from lossy‐context surprisal as a special case of a novel, more general principle called information locality. (shrink)

A central concern of the cognitive science of language since its origins has been the concept of the linguistic system. Recent approaches to the system concept in language point to the exceedingly complex relations that hold between many kinds of interdependent systems, but it can be difficult to know how to proceed when “everything is connected.” This paper offers a framework for tackling that challenge by identifying *scale* as a conceptual mooring for the interdisciplinary study of language systems. The paper (...) begins by defining the scale concept—simply, the possibility for a measure to be larger or smaller in different instances of a system, such as a phonemic inventory, a word's frequency value in a corpus, or a speaker population. We review sites of scale difference in and across linguistic subsystems, drawing on findings from linguistic typology, grammatical description, morphosyntactic theory, psycholinguistics, computational corpus work, and social network demography. We consider possible explanations for scaling differences and constraints in language. We then turn to the question of *dependencies between* sites of scale difference in language, reviewing four sample domains of scale dependency: in phonological systems, across levels of grammatical structure (Menzerath's Law), in corpora (Zipf's Law and related issues), and in speaker population size. Finally, we consider the implications of the review, including the utility of a scale framework for generating new questions and inspiring methodological innovations and interdisciplinary collaborations in cognitive-scientific research on language. (shrink)

How good are we at understanding what others communicate? It often seems to us, at least, that we understand quite well what others convey when speaking in a familiar language. However, a growing body of evidence from the psychology of language suggests that in various communicative settings comprehenders routinely form linguistic representations that are underdetermined, “sketchy”, “shallow” or imprecise, often without noticing it. The paper discusses some important consequences of this evidence. Following recent discussions in this strand of research, I (...) outline how the evidence is currently best interpreted as supporting a view on which operating at a certain level of imprecision and underdetermination is a functional feature of the system responsible for comprehension of linguistic utterances in humans. That this kind of imprecision and underdetermination is part and parcel of linguistic interactions, makes the exact success rate of comprehension particularly hard to estimate. This poses a unique and interesting challenge for assessing the quality of linguistic comprehension. Understanding what a speaker intended to convey with a linguistic utterance may be less transparent than it appears to us. I will discuss the extent to which this evidence may lead to pessimism about how good we are at comprehending what others communicate. However, as I will argue in the last part of the paper, in various cases language users can be sensitive to some types of imprecision and underdetermination in comprehension and make up for it by means of various forms of post hoc deliberation. I will describe some such clarificatory contexts and end by charting a map of important issues that require further investigation. (shrink)

Biosemiosis is a process of choice-making between simultaneously alternative options. It is well-known that, when sufficiently young children encounter a new word, they tend to interpret it as pointing to a meaning that does not have a word yet in their lexicon rather than to a meaning that already has a word attached. In previous research, the strategy was shown to be optimal from an information theoretic standpoint. In that framework, interpretation is hypothesized to be driven by the minimization of (...) a cost function: the option of least communication cost is chosen. However, the information theoretic model employed in that research neither explains the weakening of that vocabulary learning bias in older children or polylinguals nor reproduces Zipf’s meaning-frequency law, namely the non-linear relationship between the number of meanings of a word and its frequency. Here we consider a generalization of the model that is channeled to reproduce that law. The analysis of the new model reveals regions of the phase space where the bias disappears consistently with the weakening or loss of the bias in older children or polylinguals. The model is abstract enough to support future research on other levels of life that are relevant to biosemiotics. In the deep learning era, the model is a transparent low-dimensional tool for future experimental research and illustrates the predictive power of a theoretical framework originally designed to shed light on the origins of Zipf’s rank-frequency law. (shrink)

Discovering the meaning of novel communicative cues is challenging and amounts to navigating an unbounded hypothesis space. Several theories posit that this problem can be simplified by relying on positive expectations about the cognitive utility of communicated information. These theories imply that learners should assume that novel communicative cues tend to have low processing costs and high cognitive benefits. We tested this hypothesis in three studies in which toddlers (N = 90) searched for a reward hidden in one of several (...) containers. In all studies, an adult communicated the reward's location with an unfamiliar and ambiguous cue. We manipulated the processing costs (operationalized as inferential chain length) and cognitive benefits (operationalized as informativeness) of the possible interpretations of the cues. Toddlers processing of novel communicative cues were guided by expectations of low processing costs (Study 1) and high cognitive benefits (Studies 2 and 3). More specifically, toddlers treated novel cues as if they were easy to process, informative, and accurate, even when provided with repeated evidence to the contrary. These results indicate that, from toddlerhood onward, expectations of cognitive utility shape the processing of novel communicative cues. These data also reveal that toddlers, who are in the process of learning the language and communicative conventions of people around them, exert a pressure favoring cognitive efficiency in communicative systems. (shrink)