scholarly journals Assessing Spoken Word Recognition in Children Who Are Deaf or Hard of Hearing: A Translational Approach

2012 ◽  
Vol 23 (06) ◽  
pp. 464-475 ◽  
Author(s):  
Karen Iler Kirk ◽  
Lindsay Prusick ◽  
Brian French ◽  
Chad Gotch ◽  
Laurie S. Eisenberg ◽  
...  
Keyword(s):  
Word Recognition ◽  
Real World ◽  
Hard Of Hearing ◽  
Recognition Performance ◽  
Spoken Word Recognition ◽  
Current Model ◽  
Spoken Word ◽  
Assessment Tools ◽  
Visual Speech ◽  
Research Activities

Under natural conditions, listeners use both auditory and visual speech cues to extract meaning from speech signals containing many sources of variability. However, traditional clinical tests of spoken word recognition routinely employ isolated words or sentences produced by a single talker in an auditory-only presentation format. The more central cognitive processes used during multimodal integration, perceptual normalization, and lexical discrimination that may contribute to individual variation in spoken word recognition performance are not assessed in conventional tests of this kind. In this article, we review our past and current research activities aimed at developing a series of new assessment tools designed to evaluate spoken word recognition in children who are deaf or hard of hearing. These measures are theoretically motivated by a current model of spoken word recognition and also incorporate “real-world” stimulus variability in the form of multiple talkers and presentation formats. The goal of this research is to enhance our ability to estimate real-world listening skills and to predict benefit from sensory aid use in children with varying degrees of hearing loss.

Lexical neighborhoods and phonological confusability in cross-dialect word recognition in noise

2010 ◽  
Vol 1 (1) ◽  
Author(s):  
Cynthia G. Clopper ◽  
Janet B. Pierrehumbert ◽  
Terrin N. Tamati
Keyword(s):  
Word Recognition ◽  
Target Word ◽  
Recognition Performance ◽  
Spoken Word Recognition ◽  
Spoken Word ◽  
Neighborhood Density ◽  
Minimal Pair ◽  
Dialect Variation ◽  
Vowel Recognition ◽  
Stimulus Materials

AbstractLexical neighborhood density is a well-known factor affecting phonological categorization in spoken word recognition. The current study examined the interaction between lexical neighborhood density and dialect variation in spoken word recognition in noise. The stimulus materials were real English words produced in two regional American English dialects. To manipulate lexical neighborhood density, target words were selected so that predicted phonological confusions across dialects resulted in real English words in the word-competitor condition and did not result in real English words in the nonword-competitor condition. Word and vowel recognition performance were more accurate in the nonword-competitor condition than the word-competitor condition for both talker dialects. An examination of the responses to specific vowels revealed the role of dialect variation in eliciting this effect. When the predicted phonological confusions were real lexical neighbors, listeners could respond with either the target word or the confusable minimal pair, and were more likely than expected to produce a minimal pair differing from the target by one vowel. When the predicted phonological confusions were not real words, however, the listeners exhibited less lexical competition and responded with the target word or a minimal pair differing by one consonant.

scholarly journals Investigating Speechreading and Deafness

2010 ◽  
Vol 21 (03) ◽  
pp. 163-168 ◽  
Author(s):  
Edward T. Auer
Keyword(s):  
Individual Differences ◽  
Word Recognition ◽  
Spoken Word Recognition ◽  
Theoretical Framework ◽  
Spoken Word ◽  
Visual Speech ◽  
Sufficient Information ◽  
Successful Communication ◽  
Auditory Word ◽  
Auditory Word Recognition

Background: The visual speech signal can provide sufficient information to support successful communication. However, individual differences in the ability to appreciate that information are large, and relatively little is known about their sources. Purpose: Here a body of research is reviewed regarding the development of a theoretical framework in which to study speechreading and individual differences in that ability. Based on the hypothesis that visual speech is processed via the same perceptual-cognitive machinery as auditory speech, a theoretical framework was developed by adapting a theoretical framework originally developed for auditory spoken word recognition. Conclusion: The evidence to date is consistent with the conclusion that visual spoken word recognition is achieved via a process similar to auditory word recognition provided differences in perceptual similarity are taken into account. Words perceptually similar to many other words and that occur infrequently in the input stream are at a distinct disadvantage within this process. The results to date are also consistent with the conclusion that deaf individuals, regardless of speechreading ability, recognize spoken words via a process similar to individuals with hearing.

scholarly journals The neural dynamics of semantic diversity in spoken word recognition: The role of alpha-beta power

2020 ◽  
Author(s):  
Priscila Borges
Keyword(s):  
Word Recognition ◽  
Fixed Effects ◽  
Information Needs ◽  
Time Window ◽  
Recognition Performance ◽  
Spoken Word Recognition ◽  
Spoken Word ◽  
Event Related Potential ◽  
Beta Power ◽  
Alpha Beta

Word recognition performance is significantly affected by semantic diversity (SemD), acorpus-based measure that indexes the degree to which the contexts associated with a word are similar in meaning. Due to the prominence of SemD as a determinant of behaviour, it is important to understand its neural correlates, but these remain underexplored. To address thisgap, this study examines whether and how SemD information is reflected in alpha-beta power dynamics during spoken word recognition. Given previous evidence linking stronger alpha-beta power decreases to semantically richer words, high-SemD words were predicted to elicit stronger alpha-beta power decreases relative to low-SemD words. Electroencephalographic data were recorded while 13 older adults performed a word-picture verification task. Average alpha-beta (10–20 Hz) power around 400–600 ms post-word onset served as the dependentvariable in linear mixed models whose fixed effects included SemD and other psycholinguistic variables. Results showed that SemD was not a significant predictor whenposterior sites were considered. However, when anterior sites and a later time window were examined, a significant effect of SemD was found, with higher scores predicting stronger alpha-beta power decreases. Additional analyses on event-related potential responses around 300–500 ms post-stimulus showed no effects of SemD. These findings provide the first insights into the electrophysiological signature of SemD and corroborate previous reports of stronger alpha-beta power decreases when more lexical-semantic information needs to beretrieved from memory. The null results are discussed in view of a few methodologicalaspects, which could be explored in future studies.

scholarly journals Contra assertions, feedback improves word recognition

2021 ◽  
Author(s):  
James Magnuson ◽  
Samantha Grubb ◽  
Anne Marie Crinnion ◽  
Sahil Luthra ◽  
Phoebe Gaston
Keyword(s):  
Word Recognition ◽  
Speech Processing ◽  
Recognition Performance ◽  
Spoken Word Recognition ◽  
Spoken Word ◽  
Feedback Signal ◽  
Activation Model ◽  
Trace Model ◽  
Interactive Activation ◽  
Joint Probabilities

Norris and Cutler (in press) revisit their arguments that (lexical-to-sublexical) feedback cannot improve word recognition performance, based on the assumption that feedback must boost signal and noise equally. They also argue that demonstrations that feedback improves performance (Magnuson, Mirman, Luthra, Strauss, & Harris, 2018) in the TRACE model of spoken word recognition (McClelland & Elman, 1986) were artifacts of converting activations to response probabilities. We first evaluate their claim that feedback in an interactive activation model must boost noise and signal equally. This is not true in a fully interactive activation model such as TRACE, where the feedback signal does not simply mirror the feedforward signal; it is instead shaped by joint probabilities over lexical patterns, and the dynamics of lateral inhibition. Thus, even under high levels of noise, lexical feedback will selectively boost signal more than noise. We demonstrate that feedback promotes faster word recognition and preserves accuracy under noise whether one uses raw activations or response probabilities. We then document that lexical feedback selectively boosts signal (i.e., lexically-coherent series of phonemes) more than noise by tracking sublexical (phoneme) activations under noise with and without feedback. Thus, feedback in a model like TRACE does improve word recognition, exactly by selective reinforcement of lexically-coherent signal. We conclude that whether lexical feedback is integral to human speech processing is an empirical question, and briefly review a growing body of work at behavioral and neural levels that is consistent with feedback and inconsistent with autonomous (non-feedback) architectures.

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