Verbatim sentence recall is widely used to test the language competence of native and non-native speakers since it involves comprehension and production of connected speech. However, we assume that, to maintain surface information, sentence recall relies particularly on attentional resources, which differentially affects native and non-native speakers. Since even in near-natives language processing is less automatized than in native speakers, processing a sentence in a foreign language plus retaining its surface may result in a cognitive overload. We contrasted sentence recall performance of German native speakers with that of highly proficient non-natives. Non-natives recalled the sentences significantly poorer than the natives, but performed equally well on a cloze test. This implies that sentence recall underestimates the language competence of good non-native speakers in mixed groups with native speakers. The findings also suggest that theories of sentence recall need to consider both its linguistic and its attentional aspects.
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http://dx.doi.org/10.3389/fpsyg.2015.00063 | DOI Listing |
Sci Rep
January 2025
University of Ghana, P.O. Box 134, Legon-Accra, Ghana.
Sentiment analysis has become a difficult and important task in the current world. Because of several features of data, including abbreviations, length of tweet, and spelling error, there should be some other non-conventional methods to achieve the accurate results and overcome the current issue. In other words, because of those issues, conventional approaches cannot perform well and accomplish results with high efficiency.
View Article and Find Full Text PDFJ Am Med Inform Assoc
December 2024
Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, United States.
Objective: To detect and classify features of stigmatizing and biased language in intensive care electronic health records (EHRs) using natural language processing techniques.
Materials And Methods: We first created a lexicon and regular expression lists from literature-driven stem words for linguistic features of stigmatizing patient labels, doubt markers, and scare quotes within EHRs. The lexicon was further extended using Word2Vec and GPT 3.
J Pathol Inform
January 2025
Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, United States of America.
With the increasing utilization of exome and genome sequencing in clinical and research genetics, accurate and automated extraction of human phenotype ontology (HPO) terms from clinical texts has become imperative. Traditional methods for HPO term extraction, such as PhenoTagger, often face limitations in coverage and precision. In this study, we propose a novel approach that leverages large language models (LLMs) to generate synthetic sentences with clinical context, which were semantically encoded into vector embeddings.
View Article and Find Full Text PDFOpen Mind (Camb)
December 2024
University of Bern, Bern, Switzerland.
Task adaptation, characterized by a progressive increase in speed throughout experimental trials, has been extensively observed across various paradigms. Yet, the underlying mechanisms driving this phenomenon remain unclear. According to the learning-based explanation, participants are implicitly learning, becoming more proficient over time.
View Article and Find Full Text PDFCereb Cortex
December 2024
Max Planck Institute for Psycholinguistics, Wundtlaan 1, Nijmegen 6525XD, The Netherlands.
The neural representations for compositional processing have so far been mostly studied during sentence comprehension. In an fMRI study of sentence production, we investigated the brain representations for compositional processing during speaking. We used a rapid serial visual presentation sentence recall paradigm to elicit sentence production from the conceptual memory of an event.
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