Compared to the large body of work on lexical access, little research has been done on grammatical encoding in language production. An exception is the generation of subject-verb agreement. Here, two key findings have been reported: (1) speakers make more agreement errors when the head and local noun of a phrase mismatch in number than when they match [e.g., the key to the cabinet(s)]; and (2) this attraction effect is asymmetric, with stronger attraction for singular than for plural head nouns. Although these findings are robust, the cognitive processes leading to agreement errors and their significance for the generation of correct agreement are not fully understood. We propose that future studies of agreement, and grammatical encoding in general, may benefit from using paradigms that tightly control the variability of the lexical content of the material. We report two experiments illustrating this approach. In both of them, the experimental items featured combinations of four nouns, four color adjectives, and two prepositions. In Experiment 1, native speakers of Dutch described pictures in sentences such as the circle next to the stars is blue. In Experiment 2, they carried out a forced-choice task, where they read subject noun phrases (e.g., the circle next to the stars) and selected the correct verb-phrase (is blue or are blue) with a button press. Both experiments showed an attraction effect, with more errors after subject phrases with mismatching, compared to matching head and local nouns. This effect was stronger for singular than plural heads, replicating the attraction asymmetry. In contrast, the response times recorded in Experiment 2 showed similar attraction effects for singular and plural head nouns. These results demonstrate that critical agreement phenomena can be elicited reliably in lexically reduced contexts. We discuss the theoretical implications of the findings and the potential and limitations of studies using lexically simple materials.
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http://dx.doi.org/10.3389/fpsyg.2014.00783 | DOI Listing |
Brief Funct Genomics
January 2025
Department of Computer Science & Engineering, University of Kalyani, Kalyani-741235, India.
Deoxyribonucleic acid (DNA) or ribonucleic acid (RNA) sequence compressors for novel species frequently face challenges when processing wide-scale raw, FASTA, or multi-FASTA structured data. For years, molecular sequence databases have favored the widely used general-purpose Gzip and Zstd compressors. The absence of sequence-specific characteristics in these encoders results in subpar performance, and their use depends on time-consuming parameter adjustments.
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December 2024
Tecnológico de Monterrey, Institute of Advanced Materials for Sustainable Manufacturing, Colonia Nuevo México, Zapopan, Jal.
This paper uses a multi-head neural transformer to present the text-to-text translation/interpretation of Sign Language (SL) in the context of glosses (written SL). A Spanish to Mexican Sign Language (MSL) gloss dataset was built based on simple and compound sentences and the corresponding interpretation in MSL gloss. The interpretation process was achieved by implementing state-of-the-art tools in the natural language processing (NLP) field called neural transformers.
View Article and Find Full Text PDFPeerJ Comput Sci
September 2024
Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
Background: The Automatic Essay Score (AES) prediction system is essential in education applications. The AES system uses various textural and grammatical features to investigate the exact score value for AES. The derived features are processed by various linear regressions and classifiers that require the learning pattern to improve the overall score.
View Article and Find Full Text PDFJ Neurosci
November 2024
Cognitive Neuroscience Laboratory - Australian Research Centre for Interactive and Virtual Environments, University of South Australia, Adelaide, Australia.
Front Hum Neurosci
October 2024
School of Languages and Linguistics, Faculty of Arts, The University of Melbourne, Melbourne, VIC, Australia.
Introduction: Perceptual representations in language comprehension were examined using sentence-picture verification tasks. However, concerns have been raised regarding the suitability of concrete pictures for representing abstract concepts compared to image-schematic diagrams. To assess the perceptual representations of spatial and abstract domains in both first language (L1) and second language (L2) processing, the study tests bilingual speakers' mental imagery on the basis of the simulation-based L1 comprehension model and proposes a simulation-based L2 comprehension model, supported by empirical evidence from an innovative sentence-diagram verification paradigm.
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