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Cortical-striatal brain network distinguishes deepfake from real speaker identity.
Commun Biol
June 2024
Cognitive and Affective Neuroscience Unit, Department of Psychology, University of Zurich, Zurich, Switzerland.
Deepfakes are viral ingredients of digital environments, and they can trick human cognition into misperceiving the fake as real. Here, we test the neurocognitive sensitivity of 25 participants to accept or reject person identities as recreated in audio deepfakes. We generate high-quality voice identity clones from natural speakers by using advanced deepfake technologies.
View Article and Find Full Text PDFOld Dogs and New Tricks: Assessing Idiom Knowledge Amongst Native Speakers of Different Ages.
J Psycholinguist Res
December 2023
Department of English Language and Linguistics, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
Idioms, along with other formulaic multiword phrases, represent a substantial part of vocabulary knowledge. This study investigates how idiom knowledge develops through the adult lifespan, comparing familiarity and transparency ratings for a large set of common English idioms. A total of 237 participants, ranging from 18 to 77 years old, collectively rated 200 idioms.
View Article and Find Full Text PDFRevisiting the effect of text complexity on Continuous Discourse Tracking using synthetic speech: Old tricks with new dogs.
Clin Linguist Phon
March 2024
Speech Pathology and Audiology, Department of Nordic Studies and Linguistics, University of Copenhagen, Copenhagen, Denmark.
Continuous Discourse Tracking (CDT) is a functional test of speech perceptual ability, which has been criticised on account of the procedural variation inherent in the method. This study sought to reduce this variation by using synthetic speech, which was subsequently vocoded to simulate listening with a cochlear implant. We also assessed the complexity of three text excerpts with auditory ( = 10) and written Cloze tests ( = 10).
View Article and Find Full Text PDFStacking-BERT model for Chinese medical procedure entity normalization.
Math Biosci Eng
January 2023
National Engineering Laboratory for Internet Medical Systems and Applications, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Medical procedure entity normalization is an important task to realize medical information sharing at the semantic level; it faces main challenges such as variety and similarity in real-world practice. Although deep learning-based methods have been successfully applied to biomedical entity normalization, they often depend on traditional context-independent word embeddings, and there is minimal research on medical entity recognition in Chinese Regarding the entity normalization task as a sentence pair classification task, we applied a three-step framework to normalize Chinese medical procedure terms, and it consists of dataset construction, candidate concept generation and candidate concept ranking. For dataset construction, external knowledge base and easy data augmentation skills were used to increase the diversity of training samples.
View Article and Find Full Text PDFDetecting COVID-19-Related Fake News Using Feature Extraction.
Front Public Health
January 2022
Department of Information Systems, Faculty of Management, Comenius University Bratislava, Bratislava, Slovakia.
Since its emergence in December 2019, there have been numerous posts and news regarding the COVID-19 pandemic in social media, traditional print, and electronic media. These sources have information from both trusted and non-trusted medical sources. Furthermore, the news from these media are spread rapidly.
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