Nonsigners viewing sign language are sometimes able to guess the meaning of signs by relying on the overt connection between form and meaning, or iconicity (cf. Ortega, Özyürek, & Peeters, 2020; Strickland et al., 2015). One word class in sign languages that appears to be highly iconic is classifiers: verb-like signs that can refer to location change or handling. Classifier use and meaning are governed by linguistic rules, yet in comparison with lexical verb signs, classifiers are highly variable in their morpho-phonology (variety of potential handshapes and motion direction within the sign). These open-class linguistic items in sign languages prompt a question about the mechanisms of their processing: Are they part of a gestural-semiotic system (processed like the gestures of nonsigners), or are they processed as linguistic verbs? To examine the psychological mechanisms of classifier comprehension, we recorded the electroencephalogram (EEG) activity of signers who watched videos of signed sentences with classifiers. We manipulated the sentence word order of the stimuli (subject-object-verb [SOV] vs. object-subject-verb [OSV]), contrasting the two conditions, which, according to different processing hypotheses, should incur increased processing costs for OSV orders. As previously reported for lexical signs, we observed an N400 effect for OSV compared with SOV, reflecting increased cognitive load for linguistic processing. These findings support the hypothesis that classifiers are a linguistic part of speech in sign language, extending the current understanding of processing mechanisms at the interface of linguistic form and meaning. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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http://dx.doi.org/10.1037/xlm0000958 | DOI Listing |
BMC Public Health
January 2025
Social Determinants of Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran.
Background: Health Technology Assessment (HTA) is crucial for optimizing healthcare investments and improving system efficiency. In Iran, the rising costs of healthcare technologies and systemic inefficiencies have highlighted the need for a structured HTA framework. However, despite academic discussions, HTA has not yet been fully integrated into formal health policy.
View Article and Find Full Text PDFSci Rep
January 2025
University Institute of Computing, Chandigarh University, Punjab, India.
Automatic Sign Language Recognition Systems (ASLR) offers smooth communication between hearing-impaired and normal-hearing individuals, enhancing educational opportunities for impaired. However, it struggles with "curse of dimensionality" due to excessive features resulting in prolonged training time and exhaustive computational demand. This paper proposes technique that integrates machine learning and swarm intelligence to effectively address this issue.
View Article and Find Full Text PDFAfr J Disabil
December 2024
Department of Audiology, Faculty of Human and Community Development, University of the Witwatersrand, Braamfontein, South Africa.
Background: Parents of Deaf or hard-of-hearing (DHH) children are faced with a plethora of overwhelming decisions concerning their children, particularly during the early stages of development. Among these decisions are those concerning assistive devices and the modes of communication for their child.
Objectives: The aim of this study was to explore the perceptions of parents of DHH children towards the various modes of communication for their children within the South African context.
Ann Transl Med
December 2024
Division of Advanced Gastrointestinal and Bariatric Surgery, Mayo Clinic, Jacksonville, FL, USA.
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