Children must learn the structural biases of locative verbs in order to avoid making overgeneralisation errors (e.g., (∗)I filled water into the glass). It is thought that they use linguistic and situational information to learn verb classes that encode structural biases. In addition to situational cues, we examined whether children and adults could use the lexical distribution of nouns in the post-verbal noun phrase of transitive utterances to assign novel verbs to locative classes. In Experiment 1, children and adults used lexical distributional cues to assign verb classes, but were unable to use situational cues appropriately. In Experiment 2, adults generalised distributionally-learned classes to novel verb arguments, demonstrating that distributional information can cue abstract verb classes. Taken together, these studies show that human language learners can use a lexical distributional mechanism that is similar to that used by computational linguistic systems that use large unlabelled corpora to learn verb meaning.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.cognition.2016.05.001 | DOI Listing |
J Speech Lang Hear Res
January 2025
Department of Linguistics and Modern Languages, The Chinese University of Hong Kong, China.
Purpose: This study aims to examine the associations of phonological, lexical, and grammatical skills within and between languages in Mandarin-English bilingual preschoolers.
Method: Sixty-three Singaporean Mandarin-English bilingual children aged 3-5 years were assessed for articulation, receptive vocabulary, and receptive grammar using standardized instruments in English and compatible tools in Mandarin. Regression analyses were performed on each language outcome, with other language variables as predictors, controlling for age, nonverbal working memory, and home language environment.
J Psycholinguist Res
January 2025
Department of Comparative and General Linguistics, Faculty of Arts, University of Ljubljana, Ljubljana, Slovenia.
Deverbal formations in Greek, e.g. mi'razo 'to distribute' < 'mirazma 'distributing' are considered morphologically complex lexical items.
View Article and Find Full Text PDFPsychon Bull Rev
January 2025
Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LPNC, 38000, Grenoble, France.
It is striking that visual attention, the process by which attentional resources are allocated in the visual field so as to locally enhance visual perception, is a pervasive component of models of eye movements in reading, but is seldom considered in models of isolated word recognition. We describe BRAID, a new Bayesian word-Recognition model with Attention, Interference and Dynamics. As most of its predecessors, BRAID incorporates three sensory, perceptual, and orthographic knowledge layers together with a lexical membership submodel.
View Article and Find Full Text PDFDev Sci
March 2025
Laboratoire de Sciences Cognitives et de Psycholinguistique, Département d'Études Cognitives, ENS, EHESS, CNRS, PSL University, Paris, France.
Before they even talk, infants become sensitive to the speech sounds of their native language and recognize the auditory form of an increasing number of words. Traditionally, these early perceptual changes are attributed to an emerging knowledge of linguistic categories such as phonemes or words. However, there is growing skepticism surrounding this interpretation due to limited evidence of category knowledge in infants.
View Article and Find Full Text PDFBehav Res Methods
January 2025
University of Alabama, Tuscaloosa, AL, USA.
Perception of emotion conveyed through language is influenced by embodied experiences obtained from social interactions, which may vary across different cultures. To explore cross-cultural differences in the perception of emotion between Chinese and English speakers, this study collected norms of valence and arousal from 322 native Mandarin speakers for 4923 Chinese words translated from Warriner et al., (Behavior Research Methods, 45, 1191-1207, 2013).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!