Implementations are not conceptualizations: Revising the verb learning model. MacWhinney, B & Leinbach, J Cognition, 40(1-2):121-57, 1991.
abstract   bibtex   
In a recent issue of this journal, Pinker and Prince (1988) and Lachter and Bever (1988) presented detailed critiques of Rumelhart and McClelland's (1986) connectionist model of the child's learning of the phonological form of the English past tense. In order to address these criticisms, a new connectionist model was constructed using the back-propagation algorithm, a larger input corpus, a fuller paradigm, and a new phonological representation. This new implementation successfully addressed the criticisms of the phonological representation used by Rumelhart and McClelland. It did a much better job of learning the past tense using a fuller input set with realistic frequencies of occurrence. Ancillary simulations using the same network were able to deal with the homonymy problem and the generation of forms like "ated" from "ate". The one feature not provided by the new model was a way of modeling early correct production of irregular forms. The success of the new model can be used to help clarify the extent to which the published critiques apply to a particular connectionist implementation as opposed to fundamental principles underlying the broader connectionist conceptualization.
@Article{MacWhinney1991,
  author   = {B MacWhinney and J Leinbach},
  journal  = {Cognition},
  title    = {Implementations are not conceptualizations: {R}evising the verb learning model.},
  year     = {1991},
  number   = {1-2},
  pages    = {121-57},
  volume   = {40},
  abstract = {In a recent issue of this journal, Pinker and Prince (1988) and Lachter
	and Bever (1988) presented detailed critiques of Rumelhart and McClelland's
	(1986) connectionist model of the child's learning of the phonological
	form of the English past tense. In order to address these criticisms,
	a new connectionist model was constructed using the back-propagation
	algorithm, a larger input corpus, a fuller paradigm, and a new phonological
	representation. This new implementation successfully addressed the
	criticisms of the phonological representation used by Rumelhart and
	McClelland. It did a much better job of learning the past tense using
	a fuller input set with realistic frequencies of occurrence. Ancillary
	simulations using the same network were able to deal with the homonymy
	problem and the generation of forms like "ated" from "ate". The one
	feature not provided by the new model was a way of modeling early
	correct production of irregular forms. The success of the new model
	can be used to help clarify the extent to which the published critiques
	apply to a particular connectionist implementation as opposed to
	fundamental principles underlying the broader connectionist conceptualization.},
  keywords = {Computing Methodologies, Human, Language, Learning, Mental Processes, Models, Theoretical, Stochastic Processes, Support, U.S. Gov't, Non-P.H.S., Cognition, Linguistics, Neural Networks (Computer), Practice (Psychology), Non-U.S. Gov't, Memory, Psychological, Task Performance and Analysis, Time Factors, Visual Perception, Adult, Attention, Discrimination Learning, Female, Male, Short-Term, Mental Recall, Orientation, Pattern Recognition, Visual, Perceptual Masking, Reading, Concept Formation, Form Perception, Animals, Corpus Striatum, Shrews, P.H.S., Visual Cortex, Visual Pathways, Acoustic Stimulation, Auditory Cortex, Auditory Perception, Cochlea, Ear, Gerbillinae, Glycine, Hearing, Neurons, Space Perception, Strychnine, Adolescent, Decision Making, Reaction Time, Astrocytoma, Brain Mapping, Brain Neoplasms, Cerebral Cortex, Electric Stimulation, Electrophysiology, Epilepsy, Temporal Lobe, Evoked Potentials, Frontal Lobe, Noise, Parietal Lobe, Scalp, Child, Language Development, Psycholinguistics, Brain, Perception, Speech, Vocalization, Animal, Discrimination (Psychology), Hippocampus, Rats, Calcium, Chelating Agents, Excitatory Postsynaptic Potentials, Glutamic Acid, Guanosine Diphosphate, In Vitro, Neuronal Plasticity, Pyramidal Cells, Receptors, AMPA, Metabotropic Glutamate, N-Methyl-D-Aspartate, Somatosensory Cortex, Synapses, Synaptic Transmission, Thionucleotides, Action Potentials, Calcium Channels, L-Type, Electric Conductivity, Entorhinal Cortex, Neurological, Long-Evans, Infant, Mathematics, Statistics, Probability Learning, Problem Solving, Psychophysics, Association Learning, Child Psychology, Habituation (Psychophysiology), Probability Theory, Analysis of Variance, Semantics, Symbolism, Behavior, Eye Movements, Macaca mulatta, Prefrontal Cortex, Cats, Dogs, Haplorhini, Photic Stimulation, Electroencephalography, Nervous System Physiology, Darkness, Grasshoppers, Light, Membrane Potentials, Neural Inhibition, Afferent, Picrotoxin, Vision, Deoxyglucose, Injections, Microspheres, Neural Pathways, Rhodamines, Choice Behavior, Speech Perception, Verbal Learning, Dominance, Cerebral, Fixation, Ocular, Language Tests, Random Allocation, Comparative Study, Saguinus, Sound Spectrography, Species Specificity, Audiometry, Auditory Threshold, Calibration, Data Interpretation, Statistical, Anesthesia, General, Electrodes, Implanted, Pitch Perception, Sound Localization, Paired-Associate Learning, Serial Learning, Auditory, Age Factors, Motion Perception, Brain Injuries, Computer Simulation, Blindness, Psychomotor Performance, Color Perception, Signal Detection (Psychology), Judgment, ROC Curve, Regression Analysis, Music, Probability, Arm, Cerebrovascular Disorders, Hemiplegia, Movement, Muscle, Skeletal, Myoclonus, Robotics, Magnetoencephalography, Phonetics, Software, Speech Production Measurement, Epilepsies, Partial, Laterality, Stereotaxic Techniques, 1786671},
}
Downloads: 0
About
Documentation
Keywords
Search
Users
Terms and Conditions of Use
Privacy Policy
Sitemap
© BibBase.org 2021