The ability to combine words into novel sentences has been used to argue that humans have symbolic language production abilities. Critiques of connectionist models of language often center on the inability of these models to generalize symbolically (Fodor & Pylyshyn, 1988; Marcus, 1998). To address these issues, a connectionist model of sentence production was developed. The model had variables (role‐concept bindings) that were inspired by spatial representations (Landau & Jackendoff, 1993). In order to take advantage of these variables, a novel (...) dual‐pathway architecture with event semantics is proposed and shown to be better at symbolic generalization than several variants. This architecture has one pathway for mapping message content to words and a separate pathway that enforces sequencing constraints. Analysis of the model's hidden units demonstrated that the model learned different types of information in each pathway, and that the model's compositional behavior arose from the combination of these two pathways. The model's ability to balance symbolic and statistical behavior in syntax acquisition and to model aphasic double dissociations provided independent support for the dual‐pathway architecture. (shrink)

Theories of sentence production that involve a convergence of activation from conceptual‐semantic and syntactic‐sequential units inspired a connectionist model that was trained to produce simple sentences. The model used a learning algorithm that resulted in a sharing of responsibility (or “division of labor”) between syntactic and semantic inputs for lexical activation according to their predictive power. Semantically rich, or “heavy”, verbs in the model came to rely on semantic cues more than on syntactic cues, whereas semantically impoverished, or “light”, verbs (...) relied more on syntactic cues. When the syntactic and semantic inputs were lesioned, the model exhibited patterns of production characteristic of agrammatic and anomic aphasic patients, respectively. Anomic models tended to lose the ability to retrieve heavy verbs, whereas agrammatic models were more impaired in retrieving light verbs. These results obtained in both sentence production and single‐word naming simulations. Moreover, simulated agrammatic lexical retrieval was more impaired overall in sentences than in single‐word tasks, in agreement with the literature. The results provide a demonstration of the division‐of‐labor principle, as well as general support for the claim that connectionist learning principles can contribute to the understanding of non‐transparent neuropsychological dissociations. (shrink)

Recent years have seen a surge in accounts motivated by information theory that consider language production to be partially driven by a preference for communicative efficiency. Evidence from discourse production (i.e., production beyond the sentence level) has been argued to suggest that speakers distribute information across discourse so as to hold the conditional per-word entropy associated with each word constant, which would facilitate efficient information transfer (Genzel & Charniak, 2002). This hypothesis implies that the conditional (contextualized) probabilities of linguistic units (...) affect speakers’ preferences during production. Here, we extend this work in two ways. First, we explore how preceding cues are integrated into contextualized probabilities, a question which so far has received little to no attention. Specifically, we investigate how a cue's maximal informativity about upcoming words (the cue's effectiveness) decays as a function of the cue's recency. Based on properties of linguistic discourses as well as properties of human memory, we analytically derive a model of cue effectiveness decay and evaluate it against cross-linguistic data from 12 languages. Second, we relate the information theoretic accounts of discourse production to well-established mechanistic (activation-based) accounts: We relate contextualized probability distributions over words to their relative activation in a lexical network given preceding discourse. (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)

Many have thought that exercises of skill are intentional. The argument of the paper is that this thesis fails to account for important types of mistakes and errors. In what psychologists and linguists call “verbal slips with semantic bias”, a speaker mistakenly switches, reverses, or blends certain conceptual contents. Nevertheless, the speaker has successfully exercised an intellectual skill, insofar as her slip uses concepts in conformity to semantic and logical rules. To flesh out how one might successfully exercise skills without (...) doing so intentionally, the paper appeals to the idea of habit. Verbal slips thus show how human skillfulness has a considerably wider scope than is often supposed. (shrink)