The maternal voice appears to have a special role in infants' language processing. The current eye-tracking study investigated whether 24-month-olds (n = 149) learn novel words easier while listening to their mother's voice compared to hearing unfamiliar speakers. Our results show that maternal speech facilitates the formation of new word-object mappings across two different learning settings: a live setting in which infants are taught by their own mother or the experimenter, and a prerecorded setting in which infants hear the voice of either their own or another mother through loudspeakers. Furthermore, this study explored whether infants' pointing gestures and novel word productions over the course of the word learning task serve as meaningful indexes of word learning behavior. Infants who repeated more target words also showed a larger learning effect in their looking behavior. Thus, maternal speech and infants' willingness to repeat novel words are positively linked with novel word learning.
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Conscious Cogn
January 2025
Humane Technology Lab, Catholic University of Sacred Heart, Milan, Italy; Applied Technology for Neuro-Psychology Lab., Istituto Auxologico Italiano IRCCS, Milan, Italy. Electronic address:
Psychedelic drugs offer valuable insights into consciousness, but disentangling their causal effects on perceptual and high-level cognition is nontrivial. Technological advances in virtual reality (VR) and machine learning have enabled the immersive simulation of visual hallucinations. However, comprehensive experimental data on how these simulated hallucinations affects high-level human cognition is lacking.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Electrical Engineering, American University of Sharjah, Sharjah 26666, United Arab Emirates.
Accurately identifying and discriminating between different brain states is a major emphasis of functional brain imaging research. Various machine learning techniques play an important role in this regard. However, when working with a small number of study participants, the lack of sufficient data and achieving meaningful classification results remain a challenge.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Computer Science, Shaanxi Normal University, Xi'an 710062, China.
Music generation by AI algorithms like Transformer is currently a research hotspot. Existing methods often suffer from issues related to coherence and high computational costs. To address these problems, we propose a novel Transformer-based model that incorporates a gate recurrent unit with root mean square norm restriction (TARREAN).
View Article and Find Full Text PDFSci Rep
January 2025
Nanfang College Guangzhou, Guangzhou, 510970, China.
Named Entity Recognition (NER) is an essential component of numerous Natural Language Processing (NLP) systems, with the aim of identifying and classifying entities that have specific meanings in raw text, such as person (PER), location (LOC), and organization (ORG). Recently, Deep Neural Networks (DNNs) have been extensively applied to NER tasks owing to the rapid development of deep learning technology. However, despite their advancements, these models fail to take full advantage of the multi-level features (e.
View Article and Find Full Text PDFBr J Dev Psychol
January 2025
Department of Psychology, Trinity University, San Antonio, Texas, USA.
This study investigates whether the context in which a word is learnt affects noun and verb learning. There is mixed evidence in studies of noun learning, and no studies of background perceptual context in verb learning. Two-, three-, and four-year-olds (n = 162) saw a novel object moved in a novel way while hearing four novel words, either nouns or verbs.
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