jTRACE: A user‐friendly reimplementation and extension of the TRACE model of speech perception and spoken word recognition

2006 ◽  
Vol 119 (5) ◽  
pp. 3245-3245 ◽  
Author(s):  
Ted J. Strauss ◽  
James S. Magnuson ◽  
Harlan D. Harris
Keyword(s):  
Speech Perception ◽  
Word Recognition ◽  
Spoken Word Recognition ◽  
Spoken Word ◽  
Trace Model ◽  
User Friendly

scholarly journals jTRACE: A reimplementation and extension of the TRACE model of speech perception and spoken word recognition

2007 ◽  
Vol 39 (1) ◽  
pp. 19-30 ◽  
Author(s):  
Ted J. Strauss ◽  
Harlan D. Harris ◽  
James S. Magnuson
Keyword(s):  
Speech Perception ◽  
Word Recognition ◽  
Spoken Word Recognition ◽  
Spoken Word ◽  
Trace Model

Representations and representational specificity in speech perception and spoken word recognition

2007 ◽  
pp. 2-18 ◽  
Author(s):  
David B. Pisoni ◽  
Susannah V. Levi
Keyword(s):  
Speech Perception ◽  
Word Recognition ◽  
Spoken Word Recognition ◽  
Spoken Word ◽  
Lexical Knowledge ◽  
New Approaches ◽  
Abstract Representations ◽  
New Directions ◽  
Learning And Adaptation ◽  
New Framework

This article examines how new approaches—coupled with previous insights—provide a new framework for questions that deal with the nature of phonological and lexical knowledge and representation, processing of stimulus variability, and perceptual learning and adaptation. First, it outlines the traditional view of speech perception and identifies some problems with assuming such a view, in which only abstract representations exist. The article then discusses some new approaches to speech perception that retain detailed information in the representations. It also considers a view which rejects abstraction altogether, but shows that such a view has difficulty dealing with a range of linguistic phenomena. After providing a brief discussion of some new directions in linguistics that encode both detailed information and abstraction, the article concludes by discussing the coupling of speech perception and spoken word recognition.

scholarly journals Perception, Processing and Storage of Subphonemic and Extralinguistic Features in Spoken Word Recognition - An Argument from Language Variation and Change

2012 ◽  
Vol 16 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Elżbieta Łukasiewicz
Keyword(s):  
Speech Perception ◽  
Word Recognition ◽  
Speech Signal ◽  
Spoken Word Recognition ◽  
Language Variation ◽  
Spoken Word ◽  
Traditional View ◽  
Language Variation And Change ◽  
Processing And Storage ◽  
And Storage

Perception, Processing and Storage of Subphonemic and Extralinguistic Features in Spoken Word Recognition - An Argument from Language Variation and ChangeRecent research on speech perception and word recognition has shown that fine-grained sub-phonemic as well as speaker- and episode-specific characteristics of a speech signal are integrally connected with segmental (phonemic) information; they are all most probably processed in a non-distinct manner, and stored in the lexical memory. This view contrasts with the traditional approach holding that we operate on abstract phonemic representations extracted from a particular acoustic signal, without the need to process and store the multitude of its individual features. In the paper, I want to show that this turn towards the "particulars" of a speech event was in fact quite predictable, and the so-called traditional view would most probably have never been formulated if studies on language variation and language change-in-progress had been taken into account when constructing models of speech perception. In part one, I discuss briefly the traditional view ("abstract representations only"), its theoretical background, and outline some problems, internal to the speech perception theory, that the traditional view encounters. Part two will demonstrate that what we know about the implementation of sound changes has long made it possible to answer, once and for all, the question of integrated processing and storage of extralinguistic, phonemic and subphonemic characteristics of the speech signal.

Relations Among Linguistic and Cognitive Skills and Spoken Word Recognition in Adults With Cochlear Implants

2004 ◽  
Vol 47 (3) ◽  
pp. 496-508 ◽  
Author(s):  
Elizabeth A. Collison ◽  
Benjamin Munson ◽  
Arlene Earley Carney
Keyword(s):  
Speech Perception ◽  
Word Recognition ◽  
Cochlear Implants ◽  
Cognitive Abilities ◽  
Cognitive Skills ◽  
Spoken Word Recognition ◽  
Recognition Task ◽  
Spoken Word ◽  
Neighborhood Density ◽  
Hearing Sensitivity

This study examined spoken word recognition in adults with cochlear implants (CIs) to determine the extent to which linguistic and cognitive abilities predict variability in speech-perception performance. Both a traditional consonant-vowel-consonant (CVC)-repetition measure and a gated-word recognition measure (F. Grosjean, 1996) were used. Stimuli in the gated-word-recognition task varied in neighborhood density. Adults with CIs repeated CVC words less accurately than did age-matched adults with normal hearing sensitivity (NH). In addition, adults with CIs required more acoustic information to recognize gated words than did adults with NH. Neighborhood density had a smaller influence on gated-word recognition by adults with CIs than on recognition by adults with NH. With the exception of 1 outlying participant, standardized, norm-referenced measures of cognitive and linguistic abilities were not correlated with word-recognition measures. Taken together, these results do not support the hypothesis that cognitive and linguistic abilities predict variability in speech-perception performance in a heterogeneous group of adults with CIs. Findings are discussed in light of the potential role of auditory perception in mediating relations among cognitive and linguistic skill and spoken word recognition.

scholarly journals Speech Perception and Spoken Word Recognition: Past and Present

2002 ◽  
Vol 23 (1) ◽  
pp. 2-40 ◽  
Author(s):  
Peter W. Jusczyk ◽  
Paul A. Luce
Keyword(s):  
Speech Perception ◽  
Word Recognition ◽  
Spoken Word Recognition ◽  
Spoken Word

scholarly journals What Do Cognitive Networks Do? Simulations of Spoken Word Recognition Using the Cognitive Network Science Approach

2021 ◽  
Vol 11 (12) ◽  
pp. 1628
Author(s):  
Michael S. Vitevitch ◽  
Gavin J. D. Mullin
Keyword(s):  
Word Recognition ◽  
Network Model ◽  
Language Processing ◽  
Network Science ◽  
Spoken Word Recognition ◽  
Cognitive Networks ◽  
Spoken Word ◽  
Cognitive Network ◽  
Behavioral Studies ◽  
Trace Model

Cognitive network science is an emerging approach that uses the mathematical tools of network science to map the relationships among representations stored in memory to examine how that structure might influence processing. In the present study, we used computer simulations to compare the ability of a well-known model of spoken word recognition, TRACE, to the ability of a cognitive network model with a spreading activation-like process to account for the findings from several previously published behavioral studies of language processing. In all four simulations, the TRACE model failed to retrieve a sufficient number of words to assess if it could replicate the behavioral findings. The cognitive network model successfully replicated the behavioral findings in Simulations 1 and 2. However, in Simulation 3a, the cognitive network did not replicate the behavioral findings, perhaps because an additional mechanism was not implemented in the model. However, in Simulation 3b, when the decay parameter in spreadr was manipulated to model this mechanism the cognitive network model successfully replicated the behavioral findings. The results suggest that models of cognition need to take into account the multi-scale structure that exists among representations in memory, and how that structure can influence processing.

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