The role of reference in children's acquisition of a miniature artificial language

Nursery school children were presented with a simple miniature artificial language in one of three conditions. In the first, the stimuli to which the words referred contained an inherent lawful relationship and the language syntax reflected this relationship. In the second, the stimuli contained an inherent lawful relationship but the language syntax did not reflect this relationship. In the third, no lawful relationship existed among the stimuli to which the words referred so the language syntax imposed an arbitrary relationship among stimuli. Subjects in the first group were able to produce more correct utterances than those in the other two groups when the stimuli to which the words referred were not present, suggesting that some form of semantic mediation mechanism was being used. Evidence from novel constructions indicates that for both groups using stimuli containing an inherent lawful relation there were interactions between semantic learning mechanisms and syntax learning mechanisms.     

Structural packaging in the input to language learning: Contributions of prosodic and morphological marking of phrases to the acquisition of language

The linguistic input to language learning is usually thought to consist of simple strings of words. We argue that input must also include information about how words group into syntactic phrases. Natural languages regularly incorporate correlated cues to phrase structure, such as prosody, function words, and concord morphology. The claim that such cues are necessary for successful acquisition of syntax was tested in a series of miniature language learning experiments with adult subjects. In each experiment, when input included some cue marking the phrase structure of sentences, subjects were entirely successful in learning syntax; in contrast, when input lacked such a cue (but was otherwise identical), subjects failed to learn significant portions of syntax. Cues to phrase structure appear to facilitate learning by indicating to the learner those domains within which distributional analyses may be most efficiently pursued, thereby reducing the amount and complexity of required input data. More complex target systems place greater premiums on efficient analysis; hence, such cues may be even more crucial for acquisition of natural language syntax. We suggest that the finding that phrase structure cues are a necessary aspect of language input reflects the limited capacities of human language learners; languages may incorporate structural cues in part to circumvent such limitations and ensure successful acquisition.     

Précis of Foundations of language: brain, meaning, grammar, evolution

The goal of this study is to reintegrate the theory of generative grammar into the cognitive sciences. Generative grammar was right to focus on the child's acquisition of language as its central problem, leading to the hypothesis of an innate Universal Grammar. However, generative grammar was mistaken in assuming that the syntactic component is the sole course of combinatoriality, and that everything else is "interpretive." The proper approach is a parallel architecture, in which phonology, syntax, and semantics are autonomous generative systems linked by interface components. The parallel architecture leads to an integration within linguistics, and to a far better integration with the rest of cognitive neuroscience. It fits naturally into the larger architecture of the mind/brain and permits a properly mentalistic theory of semantics. It results in a view of linguistic performance in which the rules of grammar are directly involved in processing. Finally, it leads to a natural account of the incremental evolution of the language capacity.     

Subjectivity as Encounter: Feminine Ethics in the Work of Bracha Lichtenberg‐Ettinger and Anne Enright

The fragility of the subject is a recurring issue in the work of Anne Enright, one of Ireland's most remarkable and innovative writers. It is this specific interest, together with her attempt to make women into subjects, that inevitably links her work to Bracha Lichtenberg‐Ettinger's theory of the matrixial borderspace, a feminine sphere that coexists with the Lacanian symbolic order and that, even before our entrance into this linguistic system, informs our subjectivity. By turning to a point in time before language—the encounter between “self” and “other” during pregnancy—both Enright and Ettinger test the boundaries of and the gaps within the linguistic system. It is the going before language that ultimately enables both to go beyond some of the most persistent dualisms present within the linguistic system and to create room for an alternative—a feminine—understanding of the ethical relationality between self and other.     

Statistical models of syntax learning and use

This paper shows how to define probability distributions over linguistically realistic syntactic structures in a way that permits us to define language learning and language comprehension as statistical problems. We demonstrate our approach using lexical‐functional grammar (LFG), but our approach generalizes to virtually any linguistic theory. Our probabilistic models are maximum entropy models. In this paper we concentrate on statistical inference procedures for learning the parameters that define these probability distributions. We point out some of the practical problems that make straightforward ways of estimating these distributions infeasible, and develop a “pseudo‐likelihood” estimation procedure that overcomes some of these problems. This method raises interesting questions concerning the nature of the data available to a language learner and the modularity of language learning and processing.     

The simpler syntax hypothesis

What roles do syntax and semantics have in the grammar of a language? What are the consequences of these roles for syntactic structure, and why does it matter? We sketch the Simpler Syntax Hypothesis, which holds that much of the explanatory role attributed to syntax in contemporary linguistics is properly the responsibility of semantics. This rebalancing permits broader coverage of empirical linguistic phenomena and promises a tighter integration of linguistic theory into the cognitive scientific enterprise. We suggest that the general perspective of the Simpler Syntax Hypothesis is well suited to approaching language processing and language evolution, and to computational applications that draw upon linguistic insights.     

Connectionist Models and Linguistic Theory: Investigations of Stress Systems in Language

We question the widespread assumption that linguistic theory should guide the formulation of mechanistic accounts of human language processing. We develop a pseudo-linguistic theory for the domain of linguistic stress, based on observation of the learning behavior of a perceptron exposed to a variety of stress patterns. There are significant similarities between our analysis of perception stress learning and metrical phonology, the linguistic theory of human stress. Both approaches attempt to identify salient characteristics of the stress systems under examination without reference to the workings of the underlying processor. Our theory and computer simulations exhibit some strikingly suggestive correspondences with metrical theory. We show, however, that our high-level pseudo-linguistic account bears no causal relation to processing in the perception, and provides little insight into the nature of this processing. Because of the persuasive similarities between the nature of our theory and linguistic theorizing, we suggest that linguistic theory may be in much the same position. Contrary to the usual assumption, it may not provide useful guidance in attempts to identify processing mechanisms underlying human language.     

The syntax of event structure.

In this paper we examine the role of events within a theory of lexical semantics. We propose a configurational theory of event structure and examine how it contributes to a lexical semantic theory for natural language. In particular, we argue that an event structure can provide a distinct and useful level of representation for linguistic analysis involving the aspectual properties of verbs, adverbial scope, the role of argument structure, and the mapping from the lexicon to syntax.     

The Propositional vs. Hermeneutic Models of Cross-Cultural Understanding

Abstract

What the authors attempts to address in this paper is a Kantian question: not whether, but how is cross-cultural understanding possible? And specifically, what is a more effective approach for cross-cultural understanding? The answer lies in an analysis of two different models of cross-cultural understanding, that is, propositional and hermeneutic understanding. To begin with, the authors presents a linguistic interpretation of culture, i.e., a culture as a linguistically formulated and transmitted symbolic system with its conceptual core as a scheme of basic cultural presuppositions. Such a symbolic system is referred to as a cultural language. After exploring the essential role of cultural presuppositions in cross-cultural understanding, the authors discusses the traditional model of cross-cultural understanding, namely, the propositional model. Through critically examining the two popular versions of the propositional model, i.e., the projective approach and the adoptive approach to cross-cultural understanding, it is found that cross-cultural propositional understanding is doomed to failure. To move us beyond the absolutism-relativism trap embedded within propositional understanding, the authors first introduces and discusses Hans-Georg Gadamer’s hermeneutic understanding, and then applies Hans-Georg Gadamer’s hermeneutic model of understanding to cross-cultural understanding. It is finally concluded that cross-cultural understanding is essentially hermeneutic – including the case of cultural learning, not propositional. Therefore, cross-cultural understanding is hermeneutically possible.     

When learners surpass their models: the acquisition of American Sign Language from inconsistent input

The present study examines the impact of highly inconsistent input on language acquisition. The American deaf community provides a unique opportunity to observe children exposed to nonnative language models as their only linguistic input. This research is a detailed case study of one child acquiring his native language in such circumstances. It asks whether this child is capable of organizing a natural language out of input data that are not representative of certain natural language principles. Simon is a deaf child whose deaf parents both learned American Sign Language (ASL) after age 15. Simon's only ASL input is provided by his late-learner parents. The study examines Simon's performance at age 7 on an ASL morphology task, compared with eight children who have native signing parents, and also compared with Simon's own parents. The results show that Simon's production of ASL substantially surpasses that of his parents. Simon's parents, like other late learners of ASL, perform below adult native signing criteria, with many inconsistencies and errors in their use of ASL morphology. In contrast, Simon's performance is much more regular, and in fact on most ASL morphemes is equal to that of children exposed to a native signing model. The results thus indicate that Simon is capable of acquiring a regular and orderly morphological rule system for which his input provides only highly inconsistent and noisy data. In addition, the results provide some insight into the mechanisms by which such learning may occur. Although the ASL situation is rare, it reveals clues that may contribute to our understanding of the human capacity for language learning.     

The Explicit and Implicit Domains in Psychoanalytic Change

New research findings of the development and organization of the mind, brain, and behavior bolster the ongoing relational- or intersubjective-field paradigmatic revision of psychoanalytic theory. A multisystems view of learning, memory, and knowledge provide us with a more complex picture of information processing that has fundamental implications for a psychoanalytic theory of therapeutic action.

If the implicit and explicit learning/memory systems are viewed as parallel processes, not easily translatable from one to the other, then new implicit relational experience carries considerably more power as compared to explicit/declarative processing in changing and establishing new implicit mental models. When these cognitive processing systems are viewed as more closely interconnected with a developmental emphasis on connecting them through language, then exploratory/interpretive work becomes more central. REM, dream, infant, and cognitive research evidence suggests that imagistic symbolic capacity exists at birth. Learning and remembering using imagistic symbolic processing could suggest a more easily translatable connection with later developed verbal symbolic processing and a closer, although varied, interconnection between implicit and explicit (symbolic) memory systems.

Explicit attitudes are more directly modifiable through an explicit/declarative focus. Implicit mental models, it is proposed, are variably modifiable through two different change processes: (1) accommodation or transformation of expectancies through new implicit procedural experience (not requiring explicit focus) and (2) diminished activation and increased capacity to deactivate implicit mental models through explicit/declarative processing and the establishment of contrasting implicit models through new implicit procedural experience.     

Probabilistic models of language processing and acquisition

Probabilistic methods are providing new explanatory approaches to fundamental cognitive science questions of how humans structure, process and acquire language. This review examines probabilistic models defined over traditional symbolic structures. Language comprehension and production involve probabilistic inference in such models; and acquisition involves choosing the best model, given innate constraints and linguistic and other input. Probabilistic models can account for the learning and processing of language, while maintaining the sophistication of symbolic models. A recent burgeoning of theoretical developments and online corpus creation has enabled large models to be tested, revealing probabilistic constraints in processing, undermining acquisition arguments based on a perceived poverty of the stimulus, and suggesting fruitful links with probabilistic theories of categorization and ambiguity resolution in perception.     

A Computational Model of Linguistic Humor in Puns

Humor plays an essential role in human interactions. Precisely what makes something funny, however, remains elusive. While research on natural language understanding has made significant advancements in recent years, there has been little direct integration of humor research with computational models of language understanding. In this paper, we propose two information‐theoretic measures—ambiguity and distinctiveness—derived from a simple model of sentence processing. We test these measures on a set of puns and regular sentences and show that they correlate significantly with human judgments of funniness. Moreover, within a set of puns, the distinctiveness measure distinguishes exceptionally funny puns from mediocre ones. Our work is the first, to our knowledge, to integrate a computational model of general language understanding and humor theory to quantitatively predict humor at a fine‐grained level. We present it as an example of a framework for applying models of language processing to understand higher level linguistic and cognitive phenomena.     

Semantics boosts syntax in artificial grammar learning tasks with recursion

Center-embedded recursion (CER) in natural language is exemplified by sentences such as "The malt that the rat ate lay in the house." Parsing center-embedded structures is in the focus of attention because this could be one of the cognitive capacities that make humans distinct from all other animals. The ability to parse CER is usually tested by means of artificial grammar learning (AGL) tasks, during which participants have to infer the rule from a set of artificial sentences. One of the surprising results of previous AGL experiments is that learning CER is not as easy as had been thought. We hypothesized that because artificial sentences lack semantic content, semantics could help humans learn the syntax of center-embedded sentences. To test this, we composed sentences from 4 vocabularies of different degrees of semantic content due to 3 factors (familiarity, meaning of words, and semantic relationship between words). According to our results, these factors have no effect one by one but they make learning significantly faster when combined. This leads to the assumption that there were different mechanisms at work when CER was parsed in natural and in artificial languages. This finding questions the suitability of AGL tasks with artificial vocabularies for studying the learning and processing of linguistic CER.     

面向汉语认知与功能特征的语法逻辑

本文研究范畴语法的两种扩充,一是从认知特征角度的扩充,将范畴语法扩充为认知特征范畴语法,通过具有完全性的逻辑证明解决了一些不合语言事实的句子判别问题;二是从功能特征角度的扩充,提出逻辑推理的形式和进一步将二者统一的可能性问题。     

What artificial grammar learning reveals about the neurobiology of syntax

In this paper we examine the neurobiological correlates of syntax, the processing of structured sequences, by comparing FMRI results on artificial and natural language syntax. We discuss these and similar findings in the context of formal language and computability theory. We used a simple right-linear unification grammar in an implicit artificial grammar learning paradigm in 32 healthy Dutch university students (natural language FMRI data were already acquired for these participants). We predicted that artificial syntax processing would engage the left inferior frontal region (BA 44/45) and that this activation would overlap with syntax-related variability observed in the natural language experiment. The main findings of this study show that the left inferior frontal region centered on BA 44/45 is active during artificial syntax processing of well-formed (grammatical) sequence independent of local subsequence familiarity. The same region is engaged to a greater extent when a syntactic violation is present and structural unification becomes difficult or impossible. The effects related to artificial syntax in the left inferior frontal region (BA 44/45) were essentially identical when we masked these with activity related to natural syntax in the same subjects. Finally, the medial temporal lobe was deactivated during this operation, consistent with the view that implicit processing does not rely on declarative memory mechanisms that engage the medial temporal lobe. In the context of recent FMRI findings, we raise the question whether Broca’s region (or subregions) is specifically related to syntactic movement operations or the processing of hierarchically nested non-adjacent dependencies in the discussion section. We conclude that this is not the case. Instead, we argue that the left inferior frontal region is a generic on-line sequence processor that unifies information from various sources in an incremental and recursive manner, independent of whether there are any processing requirements related to syntactic movement or hierarchically nested structures. In addition, we argue that the Chomsky hierarchy is not directly relevant for neurobiological systems.     

On strong anticipation

We examine Dubois’s [Dubois, D., 2003. Mathematical foundations of discrete and functional systems with strong and weak anticipations. Lecture Notes in Computer Science 2684, 110–132.] distinction between weak anticipation and strong anticipation. Anticipation is weak if it arises from a model of the system via internal simulations. Anticipation is strong if it arises from the system itself via lawful regularities embedded in the system’s ordinary mode of functioning. The assumption of weak anticipation dominates cognitive science and neuroscience and in particular the study of perception and action. The assumption of strong anticipation, however, seems to be required by anticipation’s ubiquity. It is, for example, characteristic of homeostatic processes at the level of the organism, organs, and cells. We develop the formal distinction between strong and weak anticipation by elaboration of anticipating synchronization, a phenomenon arising from time delays in appropriately coupled dynamical systems. The elaboration is conducted in respect to (a) strictly physical systems, (b) the defining features of circadian rhythms, often viewed as paradigmatic of biological behavior based in internal models, (c) Pavlovian learning, and (d) forward models in motor control. We identify the common thread of strongly anticipatory systems and argue for its significance in furthering understanding of notions such as “internal”, “model” and “prediction”.     

How language does (and does not) relate to theory of mind: A longitudinal study of syntax,semantics, working memory and false belief

Forty‐four children (mean 3.8 years) were given three false belief, a working memory, and four language tasks (each designed to tap a different aspect of syntax or semantics), and were tested again 6 months later. Once the range of scores in the language and false belief tasks were equated, there was a bidirectional relation between language and theory of mind. There was no evidence for syntax playing a unique role in the contribution of language to theory of mind. No one measure of syntax or semantics was more likely than any other to predict later false belief. Nor was false belief related more to one aspect of later language (syntax vs. semantics) than another. Our data, taken with other findings, are consistent with the idea that both syntax and semantics contribute to false belief understanding. Working memory did not mediate the relation between language and theory of mind, nor did it facilitate later false belief.