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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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Abstract:
This work is licensed under a Creative Commons Attribution 4.0 International License. ; Phonological alternation (sound change depending on the phonological environment) poses challenges to spoken word recognition models. Mandarin Chinese T3 sandhi is such a phenomenon in which a tone 3 (T3) changes into a tone 2 (T2) when followed by another T3. In a mismatch negativity (MMN) study examining Mandarin Chinese T3 sandhi, participants passively listened to either a T2 word [tʂu2 je4] /tʂu2 je4/, a T3 word [tʂu3 je4] /tʂu3 je4/, a sandhi word [tʂu2 jen3] /tʂu3 jen3/, or a mix of T3 and sandhi word standards. The deviant in each condition was a T2 word [tʂu2]. Results showed an MMN only in the T2 and T3 conditions but not in the Sandhi or Mix conditions. All conditions also yielded omission MMNs. This pattern cannot be explained based on the surface forms of standards and deviants; rather these data suggest an underspecified or underlying T3 stored linguistic representation used in spoken word processing.
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Keyword:
Event-related potentials; Lexical representation; Mandarin Chinese; Mismatch negativity; Phonological alternation; Spoken word recognition; Tone; Tone 3 sandhi
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URL: http://hdl.handle.net/1808/30540
https://doi.org/10.3389/fpsyg.2020.00646
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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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Acoustic event, spoken keyword and emotional outburst detection
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| 15 |
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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