It has been suggested that iconic graphical signs evolve into symbolic graphical signs through repeated usage. This article reports a series of interactive graphical communication experiments using a ‘pictionary’ task to establish the conditions under which the evolution might occur. Experiment 1 rules out a simple repetition based account in favor of an account that requires feedback and interaction between communicators. Experiment 2 shows how the degree of interaction affects the evolution of signs according to a process of grounding. Experiment (...) 3 confirms the prediction that those not involved directly in the interaction have trouble interpreting the graphical signs produced in Experiment 1. On the basis of these results, this article argues that icons evolve into symbols as a consequence of the systematic shift in the locus of information from the sign to the users' memory of the sign's usage supported by an interactive grounding process. (shrink)

How is linguistic communication possible? How do we come to share the same meanings of words and utterances? One classical position holds that human beings share a transcendental “platonic” ideality independent of individual cognition and language use (Frege 1948). Another stresses immanent linguistic relations (Saussure 1959), and yet another basic embodied structures as the ground for invariant aspects of meaning (Lakoff and Johnson 1999). Here we propose an alternative account in which the possibility for sharing meaning is motivated by four (...) sources of structural stability: 1) the physical constraints and affordances of our surrounding material environment, 2) biological constraints of our human bodies, 3) social normative constraints of culture and society, and 4) the local history of social interactions. These structures and constraints interact in dynamical ways in actual language usage situations: local dialogical and social dynamics motivate and stabilize the profiling of a conceptual space already highly structured by our shared biology, culture, and environment. We will substantiate this perspective with reference to recent studies in experimental pragmatics and semiotics in which participants interact linguistically to solve cooperative tasks. Three main cases will be considered: The dynamic grounding of linguistic categories, the construction of conceptual models to relate entities in a scene, and the construction of shared conceptual scales for assessing and appraising subjective experiences. (shrink)

Traditional mechanistic accounts of language processing derive almost entirely from the study of monologue. Yet, the most natural and basic form of language use is dialogue. As a result, these accounts may only offer limited theories of the mechanisms that underlie language processing in general. We propose a mechanistic account of dialogue, the interactive alignment account, and use it to derive a number of predictions about basic language processes. The account assumes that, in dialogue, the linguistic representations employed by the (...) interlocutors become aligned at many levels, as a result of a largely automatic process. This process greatly simplifies production and comprehension in dialogue. After considering the evidence for the interactive alignment model, we concentrate on three aspects of processing that follow from it. It makes use of a simple interactive inference mechanism, enables the development of local dialogue routines that greatly simplify language processing, and explains the origins of self-monitoring in production. We consider the need for a grammatical framework that is designed to deal with language in dialogue rather than monologue, and discuss a range of implications of the account. Key Words: common ground; dialogue; dialogue routines; language comprehension; language production; monitoring; perception-behavior link. (shrink)

There has been much discussion recently about the scope and limits of purely symbolic models of the mind and about the proper role of connectionism in cognitive modeling. This paper describes the symbol grounding problem : How can the semantic interpretation of a formal symbol system be made intrinsic to the system, rather than just parasitic on the meanings in our heads? How can the meanings of the meaningless symbol tokens, manipulated solely on the basis of their shapes, be grounded (...) in anything but other meaningless symbols? The problem is analogous to trying to learn Chinese from a Chinese/Chinese dictionary alone. A candidate solution is sketched: Symbolic representations must be grounded bottom-up in nonsymbolic representations of two kinds: iconic representations, which are analogs of the proximal sensory projections of distal objects and events, and categorical representations, which are learned and innate feature-detectors that pick out the invariant features of object and event categories from their sensory projections. Elementary symbols are the names of these object and event categories, assigned on the basis of their categorical representations. Higher-order symbolic representations, grounded in these elementary symbols, consist of symbol strings describing category membership relations. Connectionism is one natural candidate for the mechanism that learns the invariant features underlying categorical representations, thereby connecting names to the proximal projections of the distal objects they stand for. In this way connectionism can be seen as a complementary component in a hybrid nonsymbolic/symbolic model of the mind, rather than a rival to purely symbolic modeling. Such a hybrid model would not have an autonomous symbolic module, however; the symbolic functions would emerge as an intrinsically dedicated symbol system as a consequence of the bottom-up grounding of categories ' names in their sensory representations. Symbol manipulation would be governed not just by the arbitrary shapes of the symbol tokens, but by the nonarbitrary shapes of the icons and category invariants in which they are grounded. (shrink)

This paper explores the role of iconicity in spoken language and other human communication systems. First, we concentrate on graphical and gestural communication and show how semantically motivated iconic signs play an important role in creating such communication systems from scratch. We then consider how iconic signs tend to become simplified and symbolic as the communication system matures and argue that this process is driven by repeated interactive use of the signs. We then consider evidence for iconicity at the level (...) of the system in graphical communication and finally draw comparisons between iconicity in graphical and gestural communication systems and in spoken language. (shrink)

How might a human communication system be bootstrapped in the absence of conventional language? We argue that motivated signs play an important role (i.e., signs that are linked to meaning by structural resemblance or by natural association). An experimental study is then reported in which participants try to communicate a range of pre-specified items to a partner using repeated non-linguistic vocalization, repeated gesture, or repeated non-linguistic vocalization plus gesture (but without using their existing language system). Gesture proved more effective (measured (...) by communication success) and more efficient (measured by the time taken to communicate) than non-linguistic vocalization across a range of item categories (emotion, object, and action). Combining gesture and vocalization did not improve performance beyond gesture alone. We experimentally demonstrate that gesture is a more effective means of bootstrapping a human communication system. We argue that gesture outperforms non-linguistic vocalization because it lends itself more naturally to the production of motivated signs. (shrink)

It is widely assumed that human learning and the structure of human languages are intimately related. This relationship is frequently suggested to derive from a language-specific biological endowment, which encodes universal, but communicatively arbitrary, principles of language structure (a Universal Grammar or UG). How might such a UG have evolved? We argue that UG could not have arisen either by biological adaptation or non-adaptationist genetic processes, resulting in a logical problem of language evolution. Specifically, as the processes of language change (...) are much more rapid than processes of genetic change, language constitutes a both over time and across different human populations, and, hence, cannot provide a stable environment to which language genes could have adapted. We conclude that a biologically determined UG is not evolutionarily viable. Instead, the original motivation for UG arises because language has been shaped to fit the human brain, rather than vice versa. Following Darwin, we view language itself as a complex and interdependent which evolves under selectional pressures from human learning and processing mechanisms. That is, languages themselves are shaped by severe selectional pressure from each generation of language users and learners. This suggests that apparently arbitrary aspects of linguistic structure may result from general learning and processing biases deriving from the structure of thought processes, perceptuo-motor factors, cognitive limitations, and pragmatics. (shrink)

Memory is fleeting. New material rapidly obliterates previous material. How, then, can the brain deal successfully with the continual deluge of linguistic input? We argue that, to deal with this “Now-or-Never” bottleneck, the brain must compress and recode linguistic input as rapidly as possible. This observation has strong implications for the nature of language processing: (1) the language system must “eagerly” recode and compress linguistic input; (2) as the bottleneck recurs at each new representational level, the language system must build (...) a multilevel linguistic representation; and (3) the language system must deploy all available information predictively to ensure that local linguistic ambiguities are dealt with “Right-First-Time”; once the original input is lost, there is no way for the language system to recover. This is “Chunk-and-Pass” processing. Similarly, language learning must also occur in the here and now, which implies that language acquisition is learning to process, rather than inducing, a grammar. Moreover, this perspective provides a cognitive foundation for grammaticalization and other aspects of language change. Chunk-and-Pass processing also helps explain a variety of core properties of language, including its multilevel representational structure and duality of patterning. This approach promises to create a direct relationship between psycholinguistics and linguistic theory. More generally, we outline a framework within which to integrate often disconnected inquiries into language processing, language acquisition, and language change and evolution. (shrink)

This paper compares two explanations of the process by which human communication systems evolve: iterated learning and social collaboration. It then reports an experiment testing the social collaboration account. Participants engaged in a graphical communication task either as a member of a community, where they interacted with seven different partners drawn from the same pool, or as a member of an isolated pair, where they interacted with the same partner across the same number of games. Participants’ horizontal, pair‐wise interactions led (...) “bottom up” to the creation of an effective and efficient shared sign system in the community condition. Furthermore, the community‐evolved sign systems were as effective and efficient as the local sign systems developed by isolated pairs. Finally, and as predicted by a social collaboration account, and not by an iterated learning account, interaction was critical to the creation of shared sign systems, with different isolated pairs establishing different local sign systems and different communities establishing different global sign systems. (shrink)

This paper explores the role of iconicity in spoken language and other human communication systems. First, we concentrate on graphical and gestural communication and show how semantically motivated iconic signs play an important role in creating such communication systems from scratch. We then consider how iconic signs tend to become simplified and symbolic as the communication system matures and argue that this process is driven by repeated interactive use of the signs. We then consider evidence for iconicity at the level (...) of the system in graphical communication and finally draw comparisons between iconicity in graphical and gestural communication systems and in spoken language. (shrink)

In the last few years, researchers have begun to investigate the emergence of novel forms of human communication in the laboratory. I survey this growing line of research, which may be called experimental semiotics, from three distinct angles. First, I situate the new approach in its theoretical and historical context. Second, I review a sample of studies that exemplify experimental semiotics. Third, I present an empirical study that illustrates how the new approach can help us understand the socio‐cognitive underpinnings of (...) human communication. The main conclusion of the paper will be that, by reproducing micro samples of historical processes in the laboratory, experimental semiotics offers new powerful tools for investigating human communication as a form of joint action. (shrink)

Arbitrariness and systematicity are two of language’s most fascinating properties. Although both are characterizations of the mappings between signals and meanings, their emergence and evolution in communication systems has generally been explored independently. We present an experiment in which both arbitrariness and systematicity are probed. Participants invent signs from scratch to refer to a set of items that share salient semantic features. Through interaction, the systematic re-use of arbitrary signal elements emerges.

Languages are transmitted from person to person and generation to generation via a process of iterated learning: people learn a language from other people who once learned that language themselves. We analyze the consequences of iterated learning for learning algorithms based on the principles of Bayesian inference, assuming that learners compute a posterior distribution over languages by combining a prior (representing their inductive biases) with the evidence provided by linguistic data. We show that when learners sample languages from this posterior (...) distribution, iterated learning converges to a distribution over languages that is determined entirely by the prior. Under these conditions, iterated learning is a form of Gibbs sampling, a widely-used Markov chain Monte Carlo algorithm. The consequences of iterated learning are more complicated when learners choose the language with maximum posterior probability, being affected by both the prior of the learners and the amount of information transmitted between generations. We show that in this case, iterated learning corresponds to another statistical inference algorithm, a variant of the expectation-maximization (EM) algorithm. These results clarify the role of iterated learning in explanations of linguistic universals and provide a formal connection between constraints on language acquisition and the languages that come to be spoken, suggesting that information transmitted via iterated learning will ultimately come to mirror the minds of the learners. (shrink)

Language maps signals onto meanings through the use of two distinct types of structure. First, the space of meanings is discretized into categories that are shared by all users of the language. Second, the signals employed by the language are compositional: The meaning of the whole is a function of its parts and the way in which those parts are combined. In three iterated learning experiments using a vast, continuous, open-ended meaning space, we explore the conditions under which both structured (...) categories and structured signals emerge ex nihilo. While previous experiments have been limited to either categorical structure in meanings or compositional structure in signals, these experiments demonstrate that when the meaning space lacks clear preexisting boundaries, more subtle morphological structure that lacks straightforward compositionality—as found in natural languages—may evolve as a solution to joint pressures from learning and communication. (shrink)

Through cultural transmission, repeated learning by new individuals transforms cultural information, which tends to become increasingly compressible . Existing diffusion chain studies include in their design two processes that could be responsible for this tendency: learning and reproducing . This paper manipulates the presence of learning in a simple iterated drawing design experiment. We find that learning seems to be the causal factor behind the increase in compressibility observed in the transmitted information, while reproducing is a source of random heritable (...) innovations. Only a theory invoking these two aspects of cultural learning will be able to explain human culture's fundamental balance between stability and innovation. (shrink)