Publications

Abstract

In recent years, it has become clear that attention plays an important role in spoken word production. Some of this evidence comes from distributional analyses of reaction time (RT) in regular picture naming and picture-word interference. Yet we lack a mechanistic account of how the properties of RT distributions come to reflect attentional processes and how these processes may in turn modulate the amount of conflict between lexical representations. Here, we present a computational account according to which attentional lapses allow for existing conflict to build up unsupervised on a subset of trials, thus modulating the shape of the resulting RT distribution. Our process model resolves discrepancies between outcomes of previous studies on semantic interference. Moreover, the model's predictions were confirmed in a new experiment where participants' motivation to remain attentive determined the size and distributional locus of semantic interference in picture naming. We conclude that process modeling of RT distributions importantly improves our understanding of the interplay between attention and conflict in word production. Our model thus provides a framework for interpreting distributional analyses of RT data in picture naming tasks.

Abstract

Preparing words in speech production is normally a fast and accurate process. We generate them two or three per second in fluent conversation; and overtly naming a clear picture of an object can easily be initiated within 600 msec after picture onset. The underlying process, however, is exceedingly complex. The theory reviewed in this target article analyzes this process as staged and feedforward. After a first stage of conceptual preparation, word generation proceeds through lexical selection, morphological and phonological encoding, phonetic encoding, and articulation itself. In addition, the speaker exerts some degree of output control, by monitoring of self-produced internal and overt speech. The core of the theory, ranging from lexical selection to the initiation of phonetic encoding, is captured in a computational model, called WEAVER + +. Both the theory and the computational model have been developed in interaction with reaction time experiments, particularly in picture naming or related word production paradigms, with the aim of accounting. for the real-time processing in normal word production. A comprehensive review of theory, model, and experiments is presented. The model can handle some of the main observations in the domain of speech errors (the major empirical domain for most other theories of lexical access), and the theory opens new ways of approaching the cerebral organization of speech production by way of high-temporal-resolution imaging.

Abstract

Lexical access in speaking consists of two major steps: lemma retrieval and word-form encoding. In Roelofs (Roelofs, A. 1992a. Cognition 42. 107-142; Roelofs. A. 1993. Cognition 47, 59-87.), I described a model of lemma retrieval. The present paper extends this work by presenting a comprehensive model of the second access step, word-form encoding. The model is called WEAVER (Word-form Encoding by Activation and VERification). Unlike other models of word-form generation, WEAVER is able to provide accounts of response time data, particularly from the picture-word interference paradigm and the implicit priming paradigm. Its key features are (1) retrieval by spreading activation, (2) verification of activated information by a production rule, (3) a rightward incremental construction of phonological representations using a principle of active syllabification, syllables are constructed on the fly rather than stored with lexical items, (4) active competitive selection of syllabic motor programs using a mathematical formalism that generates response times and (5) the association of phonological speech errors with the selection of syllabic motor programs due to the failure of verification.