Running head: Wordformer (2008)
Daragh E. Sibley, David C. Plaut, Christopher T. Kello, Jeffrey L. Elman
The forms of words as they appear in text and speech are central to theories and models of lexical processing, yet current means of representing wordforms are lacking in certain key aspects. In the...
doi:10.1093/jos/ffm018 Coherence and Coreference Revisited (2008)
Andrew Kehler, Laura Kertz, Hannah Rohde, Jeffrey L. Elman
For more than three decades, research into the psycholinguistics of pronoun interpretation has argued that hearers use various interpretation ‘preferences ’ or ‘strategies ’ that are...
Event Structure and Discourse Coherence Biases in Pronoun Interpretation (2008)
Hannah Rohde, Andrew Kehler, Jeffrey L. Elman
In a story completion study involving transfer-of-possession passages (John handed a book to Bob. He _____), Stevenson et al. (1994) identified a pronoun interpretation preference that is compatible...
Learning and development in neural networks: The (2008)
importance of starting small
Journal Memory & Cognition (2008)
Ken Mcrae, Mary Hare, Jeffrey L. Elman, Todd Ferretti
A basis for generating expectancies for verbs from nouns The role of expectancy generation in sentence processing has attracted increased attention over the past several years. There has long been...
Developmental Science 11:1 (2008), pp 135–155 DOI: 10.1111/j.1467-7687.2007.00634.x Blackwell (2008)
John D. Lewis, Jeffrey L. Elman
Growth-related neural reorganization and the autism phenotype: a test of the hypothesis that altered brain growth leads to altered connectivity
Event Structure and Discourse Coherence Biases in Pronoun Interpretation (2008)
Hannah Rohde, Andrew Kehler, Jeffrey L. Elman
In a story completion study involving transfer-of-possession passages (John handed a book to Bob. He _____), Stevenson et al. (1994) identified a pronoun interpretation preference that is compatible...
James L. Mcclelland, Jeffrey L. Elman
We describe a model called the TRACE model of speech perception. The model is based on the principles of interactive activation. Information processing takes place through the excitatory and...
Jeffrey L. Elman, James L. Mcclelland
An important question in language processing is whether higher-level processes are able to interact directly with lower-level processes, as assumed by interactive models such as the TRACE model of...
The Divergent-Reconvergent Model of Serial Order Encoding and Retrieval (2008)
Danke X. Shieh, Jeffrey L. Elman
This paper presents a new connectionist model for serial order encoding and retrieval. It is based on a divergent-reconvergent structure, which encodes a list of items as a superimposed distributed...
Computational approaches to language acquisition
Coherence and Coreference Revisited (2008)
Kehler, Andrew, Kertz, Laura, Rohde, Hannah, Elman, Jeffrey L.
For more than three decades, research into the psycholinguistics of pronoun interpretation has argued that hearers use various interpretation ‘preferences’ or ‘strategies’ that are associated...
Connectionist models of cognitive development: Where next (2005)
Over the past two decades, connectionist models have generated a lively debate regarding the underlying mechanisms of cognitive development. This debate has in turn led to important empirical...
Cues, constraints, and competition in sentence processing (2005)
Jeffrey L. Elman, Mary Hare, Ken Mcrae
One of the hallmarks of human behavior is that it reflects the rapid integration of constraints from an often large number of sources, in a manner that is flexible, responsive to novel situations,...
An alternative view of the mental lexicon (2004)
An essential aspect of knowing language is knowing the words of that language. This knowledge is usually thought to reside in the mental lexicon, a kind of dictionary that contains information...
Why is that? Structural prediction and ambiguity (2004)
Douglas Rol, Jeffrey L. Elman, Victor S. Ferreira
resolution in a very large corpus of English sentences *
Admitting That Admitting Verb Sense Into Corpus (2004)
Analyses Makes Sense, Mary Hare, Ken Mcrae, Jeffrey L. Elman
this paper we address the interacting influences of meaning on structure and structure on meaning during comprehension, and the implications of these influences for the resolution of structural...
Speech Perception as a Cognitive Process: The Interactive Activation Model. (2002)
Elman,Jeffrey L., McClelland,James L.
In this paper we describe several attempts to model speech perception in terms of a processing system in which knowledge and processing is distributed over large numbers of highly interactive -- but...
Interactive Activation Models of Perception and Comprehension. (2002)
Elman,Jeffrey L., McClelland,James L.
The objective of this research is to construct a computationally sufficient, biologically plausible, and behaviorally adequate account of human information processing skills in visual and auditory...
Learning the Hidden Structure of Speech. (2002)
Elman,Jeffrey L., Zipser,David
In the work described here, we apply the back-propagation neural network learning procedure to the analysis and recognition of speech. Because this learning procedure requires only examples of...
Generalization from Sparse Input (2002)
this paper, I would like to discuss several problems that arise as a result of the following conundrum
John D. Lewis, Jeffrey L. Elman
Statistical learning, and “any account which assigns a fundamental role to segmentation, categorization, analogy, and generalization ” is rejected in Chomskyan
John D. Lewis, Jeffrey L. Elman
Based on the apparent paucity of input, and the nonobvious nature of linguistic generalizations, Chomskyan linguists assume an innate body of linguistically detailed knowledge, known as Universal...
A recurrent neural network that learns to count (1999)
Paul Rodriguez, Janet Wiles, Jeffrey L. Elman
Parallel distributed processing (PDP) architectures demonstrate a potentially radical alternative to the traditional theories of language processing that are based on serial computational models....
Connectionist Models: Proceedings of the Summer School Held in San Diego, California on 1990, (1998)
Touretzky, David S., Elman, Jeffrey L., SeJnowski, Terrence J., Hinton, Geoffrey E.
The simplicity and locality of the contrastive Hebb synapse (CHS) used in Boltzmann machine learning makes it an attractive model for real biological synapses. The slow learning exhibited by the...
Transputer Implementation of the TRACE Model of Speech Recognition. (1998)
Elman, Jeffrey L., Smith, Paul S., Dolson, Mark
We describe the accomplishments of the five-year project to develop an extended version of the TRACE model of speech recognition and to port it to a Transputer platform. We begin with an over view of...
Representation and Structure in Connectionist Models, (1998)
This paper focuses on the nature of representations in connectionist models. It addresses two issues: Can connectionist models develop representations which possess internal structure and which...
Temporal Processing with Neural Networks. (1998)
The research carried out under this contract focussed on four efforts, all involving the processing of temporal sequences by neural networks (1-3) or the effect of imposing a spatio-temporal gradient...
Gene Regulation And Biological Development In Neural Networks: An Exploratory Model (1995)
Jeffrey L. Elman, Angelo Cangelosi, Angelo Cangelosi
This paper discusses the simulation results of a model of biological development for neural networks based on a regulatory genome. The network development is controlled by genes that produce elements...
Language as a Dynamical System (1995)
Introduction Despite considerable diversity among theories about how humans process language, there are a number of fundamental assumptions which are shared by most such theories. This consensus...
Default generalization in connectionist networks (1995)
A potential problem for connectionist accounts of inflectional morphology is the need to learn a `default' inflection (Prasada & Pinker, 1993). The early connectionist work of Rumelhart...
Learning and Evolution in Neural Networks (1994)
Stefano Nolfi, Stefano Nolfi, Jeffrey L. Elman, Jeffrey L. Elman, Domenico Parisi, Domenico Parisi
The paper describes simulations on populations of neural networks that both evolve at the population level and learn at the individual level. Unlike other simulations, the evolutionary task (finding...
Analyzing Cross Connected Networks (1994)
Thomas R. Shultz, Jeffrey L. Elman
The non-linear complexities of neural networks make network solutions difficult to understand. Sanger's contribution analysis is here extended to the analysis of networks automatically generated...
Learning and development in neural networks: The importance of starting small (1993)
It is a striking fact that in humans the greatest learnmg occurs precisely at that point in time- childhood- when the most dramatic maturational changes also occur. This report describes possible...
Learning and development in neural networks: The importance of starting small (1993)
It is a striking fact that in humans the greatest learnmg occurs precisely at that point in time- childhood- when the most dramatic maturational changes also occur. This report describes possible...
Learning and development in neural networks: The importance of starting small (1993)
It is a striking fact that in humans the greatest learnmg occurs precisely at that point in time- childhood- when the most dramatic maturational changes also occur. This report describes possible...
Connectionism and the study of change (1993)
Elizabeth A. Bates, Jeffrey L. Elman
Developmental psychology and developmental neuropsychology have traditionally focused on the study of children. But these two fields are also supposed to be about the study of change, i.e. changes in...
A PDP Approach to Processing Center-Embedded Sentences (1992)
Jill Weckerly, Jeffrey L. Elman
Recent PDP models have been shown to have great promise in contributing to the understanding of the mechanisms which subserve language processing. In this paper we address the specific question of...
Distributed Representations, Simple Recurrent Networks, and Grammatical Structure (1991)
this paper I would like to focus on what I see as three of the principal challenges to a successful connectionist account of language. They are:
Distributed representations, simple recurrent networks, and grammatical structure (1991)
Abstract. In this paper three problems for a connectionist account of language are considered: 1. What is the nature of linguistic representations? 2. How can complex structural relationships such as...
Finding structure in time (1990)
Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on...
Finding structure in time (1990)
Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on...
Finding structure in time (1990)
Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implicitly by its effects on...
Learning and Evolution in Neural Networks (1990)
Stefano Nolfi, Stefano Nolfi, Jeffrey L. Elman, Jeffrey L. Elman, Domenico Parisi, Domenico Parisi
The paper describes simulations on populations of neural networks that both evolve at the population level and learn at the individual level. Unlike other simulations, the evolutionary task (finding...
Learning and Evolution in Neural Networks (1990)
Stefano Nolfi, Istituto Di Psicologia, Jeffrey L. Elman, Domenico Parisi
In this report we present the results of a series of simulations in which neural networks undergo change as a result of two forces: learning during the "lifetime" of a network, and...