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Unsupervised quantification of entity consistency between photos and text in real-world news ...
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Müller-Budack, Eric. - : Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2022
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COSMO-Onset: A Neurally-Inspired Computational Model of Spoken Word Recognition, Combining Top-Down Prediction and Bottom-Up Detection of Syllabic Onsets
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In: ISSN: 1662-5137 ; Frontiers in Systems Neuroscience ; https://hal.archives-ouvertes.fr/hal-03318691 ; Frontiers in Systems Neuroscience, Frontiers, 2021, 15, pp.653975. ⟨10.3389/fnsys.2021.653975⟩ (2021)
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Online activation of L1 Danish orthography enhances spoken word recognition of Swedish
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In: ISSN: 0332-5865 ; Nordic Journal of Linguistics ; https://hal-amu.archives-ouvertes.fr/hal-03283527 ; Nordic Journal of Linguistics, 2021, pp.1-19. ⟨10.1017/S0332586521000056⟩ (2021)
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Hand-gesture recognition based on EMG and event-based camera sensor fusion: a benchmark in neuromorphic computing
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In: ISSN: 1662-4548 ; EISSN: 1662-453X ; Frontiers in Neuroscience ; https://hal.archives-ouvertes.fr/hal-02617084 ; Frontiers in Neuroscience, Frontiers, 2020, pp.36 ; https://www.frontiersin.org/ (2020)
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Neuroplasticity in Visual Word Recognition: An Exploration of Learning-Related Behavioural and Neural Changes ...
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The temporal dynamics of first and second language processing: ERPs to spoken words in Mandarin-English bilinguals
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In: Brain and Mind Institute Researchers' Publications (2020)
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Traitement neuronal des voix et familiarité : entre reconnaissance et identification du locuteur
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The Role of Surface and Underlying Forms When Processing Tonal Alternations in Mandarin Chinese: A Mismatch Negativity Study
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Challenges in Audio Processing of Terrorist-Related Data
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In: International Conference on Multimedia Modeling ; https://hal.archives-ouvertes.fr/hal-02415176 ; International Conference on Multimedia Modeling, Springer, Jan 2019, Thessaloniki, Greece (2019)
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Challenges in Audio Processing of Terrorist-Related Data
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In: International Conference on Multimedia Modeling ; https://hal.archives-ouvertes.fr/hal-02387373 ; International Conference on Multimedia Modeling, Springer, Jan 2019, Thessaloniki, Greece (2019)
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Does the prosodic emphasis of sentential context cause deeper lexical-semantic processing?
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In: ISSN: 2327-3798 ; EISSN: 2327-3801 ; Language, Cognition and Neuroscience ; https://hal.univ-lille.fr/hal-01917002 ; Language, Cognition and Neuroscience, Taylor and Francis, 2019, 34, pp.29-42. ⟨10.1080/23273798.2018.1499945⟩ (2019)
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Abstract:
International audience ; Speakers use prosodic emphasis to express the content of their message in order to help listeners to infer meaning. By measuring event-related potentials (ERPs) to semantically congruent and incongruent final words embedded in a sentential context that was emphasised or de-emphasised, we investigated whether prosodic emphasis conveyed by a sentential context leads listeners to a finer semantic analysis. The negative shift (N400) triggered by the difficulty to combine the incongruent word with the sentence representation was increased by prosodic emphasis at an early stage. Over the later stages, the amplitude of the N400 wave was increased by prosodic emphasis of the sentential context, whatever the semantic congruency of final words. As shown by the N400 wave, emphasising a sentential context affected the lexical-semantic processing of the following word. This study provides clear evidence that prosodic emphasis plays a role in the semantic analysis of sentences by inducing a deeper analysis. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
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Keyword:
[SCCO.NEUR]Cognitive science/Neuroscience; [SCCO.PSYC]Cognitive science/Psychology; article; event related potential; human; word recognition
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URL: https://hal.univ-lille.fr/hal-01917002/document https://hal.univ-lille.fr/hal-01917002/file/Manuscript_LCN2019.pdf https://doi.org/10.1080/23273798.2018.1499945 https://hal.univ-lille.fr/hal-01917002
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Acoustic event, spoken keyword and emotional outburst detection
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Event Structure In Vision And Language
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In: Publicly Accessible Penn Dissertations (2019)
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Investigating the Electrophysiology of Long-Term Priming in Spoken Word Recognition
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In: ETD Archive (2018)
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Non-linguistic Vocalization Recognition Based on Convolutional, Long Short-Term Memory, Deep Neural Networks
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Qiu, Liang. - : eScholarship, University of California, 2018
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In: Qiu, Liang. (2018). Non-linguistic Vocalization Recognition Based on Convolutional, Long Short-Term Memory, Deep Neural Networks. UCLA: Electrical Engineering 0303. Retrieved from: http://www.escholarship.org/uc/item/1pz29229 (2018)
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Abstract Concepts and Pictures of Real-World Situations Activate One Another.
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In: Psychology Publications (2018)
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