scholarly journals Assessing lexical-semantic naming deficits using an automated machine learning approach

2021 ◽  
Author(s):  
Tatiana Tamara Schnur ◽  
Chia-Ming Lei
Keyword(s):  
Left Hemisphere ◽  
Language Production ◽  
Convergent Validity ◽  
Human Error ◽  
Semantic Knowledge ◽  
Acute Stage ◽  
Lexical Semantic ◽  
Predicting Performance ◽  
Lexical Semantic Knowledge ◽  
Left Hemisphere Stroke

After left hemisphere stroke, 20-50% of people experience language deficits, including difficulties in naming. Naming errors that are semantically related to the intended target (e.g., producing “violin” for picture HARP) indicate a potential impairment in accessing knowledge of word forms and their meanings. Understanding the cause of naming impairments is crucial to better modeling of language production as well as for tailoring individualized rehabilitation. However, evaluation of naming errors is typically by subjective and laborious dichotomous classification. As a result, these evaluations do not capture the degree of semantic similarity and are susceptible to lower inter-rater reliability because of subjectivity. We investigated whether a computational linguistic measure, word2vec (Mikolov, Chen, Corrado, & Dean, 2013) addressed these limitations by evaluating errors during object naming in a group of patients during the acute stage of a left-hemisphere stroke (N=105). Pearson correlations demonstrated excellent convergent validity of word2vec’s semantically related estimates of naming errors and independent tests of access to lexical-semantic knowledge (p’s < .0001). Further, multiple regression analysis showed word2vec’s semantically related estimates were significantly better than human error classification at predicting performance on tests of lexical-semantic knowledge (p < .001). Useful to both theorists and clinicians, word2vec provides an automated, continuous, and objective psychometric measure of access to lexical-semantic knowledge during naming.

scholarly journals Lexical Semantic Knowledge of Children with ASD—a Review Study

2021 ◽  
Author(s):  
Nufar Sukenik ◽  
Laurice Tuller
Keyword(s):  
Children With Autism ◽  
Semantic Knowledge ◽  
Future Studies ◽  
Lexical Semantic ◽  
Children With Asd ◽  
Wide Range ◽  
Lexical Semantic Knowledge ◽  
Review Study ◽  
Linguistic Impairment ◽  
Semantic Skills

AbstractStudies on the lexical semantic abilities of children with autism have yielded contradicting results. The aim of the current review was to explore studies that have specifically focused on the lexical semantic abilities of children with ASD and try to find an explanation for these contradictions. In the 32 studies reviewed, no single factor was found to affect lexical semantic skills, although children with broader linguistic impairment generally, but not universally, also showed impaired lexical semantic skills. The need for future studies with young ASD participants, with differing intellectual functioning, longitudinal studies, and studies assessing a wide range of language domains are discussed.

scholarly journals Settling into Semantic Space: An Ambiguity-Focused Account of Word-Meaning Access

2019 ◽  
Author(s):  
Jennifer M Rodd
Keyword(s):  
Dimensional Space ◽  
Word Meaning ◽  
Semantic Space ◽  
Semantic Knowledge ◽  
Vital Role ◽  
Future Research ◽  
Learning Mechanisms ◽  
Stable States ◽  
Lexical Semantic ◽  
Lexical Semantic Knowledge

Most words are ambiguous: individual wordforms (e.g., “run”) can map onto multiple different interpretations depending on their sentence context (e.g., “the athlete/politician/river runs”). Models of word-meaning access must therefore explain how listeners and readers are able to rapidly settle on a single, contextually appropriate meaning for each word that they encounter. This article presents a new account of word meaning that places semantic disambiguation at its core, and integrates evidence from a wide variety of experimental approaches to explain this key aspect of language comprehension. The model has three key characteristics. (i) Lexical-semantic knowledge is viewed as a high-dimensional space; familiar word meanings correspond to stable states within this lexical-semantic space. (ii) Multiple linguistic and paralinguistic cues can influence the settling process by which the system resolves on one of these familiar meanings. (iii) Learning mechanisms play a vital role in facilitating rapid word-meaning access by shaping and maintaining high quality lexical-semantic knowledge. Several key areas for future research are identified.

scholarly journals Lexical and semantic influences on item and order memory in immediate serial recognition: Evidence from a novel task

2006 ◽  
Vol 59 (5) ◽  
pp. 949-964 ◽  
Author(s):  
Elizabeth Jefferies ◽  
Clive Frankish ◽  
Matthew A. Lambon Ralph
Keyword(s):  
Serial Recall ◽  
Short Term Memory ◽  
Memory Task ◽  
Semantic Knowledge ◽  
Linguistic Knowledge ◽  
Immediate Serial Recall ◽  
Lexical Semantic ◽  
Item Order ◽  
Lexical Semantic Knowledge ◽  
Identity Changes

Previous studies have reported that, in contrast to the effect on immediate serial recall, lexical/semantic factors have little effect on immediate serial recognition. This has been taken as evidence that linguistic knowledge contributes to verbal short-term memory in a redintegrative process at recall. Contrary to this view, we found that lexicality, frequency, and imageability all influenced matching span. The standard matching span task, requiring changes in item order to be detected, was less susceptible to lexical/semantic factors than was a novel task involving the detection of phoneme order and hence item identity changes. Therefore, in both immediate recognition and immediate serial recall, lexical/semantic knowledge makes a greater contribution to item identity than to item order memory. Task sensitivity, and not the absence of overt recall, may have underpinned previous failures to show effects of these variables in immediate recognition. We also compared matching span for pure and unpredictable mixed lists of words and nonwords. Lexicality had a larger impact on immediate recognition for pure than for mixed lists, in line with findings for immediate serial recall. List composition affected the detection of phoneme but not item order changes in matching span; similarly, in recall, mixed lists produce more frequent word phoneme migrations but not migrations of entire items. These results point to strong similarities between immediate serial recall and recognition. Lexical/semantic knowledge may contribute to phonological stability in both tasks.

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