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Variability and stability in early language acquisition: Comparing monolingual and bilingual infants' speech perception and word recognition
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In: ISSN: 1366-7289 ; EISSN: 1469-1841 ; Bilingualism: Language and Cognition ; https://hal.archives-ouvertes.fr/hal-02566031 ; Bilingualism: Language and Cognition, Cambridge University Press (CUP), 2020, 23 (1), pp.56-71. ⟨10.1017/S1366728919000348⟩ (2020)
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Au commencement était la prosodie : du langage en émergence à l’histoire de la description de la parole
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In: https://hal.archives-ouvertes.fr/tel-03173746 ; Linguistique. Université de Toulouse Jean Jaurès, 2020 (2020)
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Quantifying Sources of Variability in Infancy Research Using the Infant-Directed-Speech Preference
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In: ADVANCES IN METHODS AND PRACTICES IN PSYCHOLOGICAL SCIENCE, vol 3, iss 1 (2020)
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Adjacent and Non-Adjacent Word Contexts Both Predict Age of Acquisition of English Words: A Distributional Corpus Analysis of Child-Directed Speech.
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In: Cognitive science, vol 44, iss 11 (2020)
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Boosting language skills of ELLs through dramatization and movement
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In: The Reading Teacher, vol 67, iss 3 (2020)
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Culture as Non-Consensus: Exploring Coherence Among Native Speakers’ Perceptions of German Expressions of Affection
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In: L2 Journal, vol 12, iss 1 (2020)
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The Russian language in France ; The Russian language in France: from the Russian community to the national education system
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In: The Soft Power of the Russian Language: Pluricentricity, Politics and Policies ; https://hal.archives-ouvertes.fr/hal-02508409 ; Arto Mustajoki; Ekaterina Protassova; Maria Yelenevskaya. The Soft Power of the Russian Language: Pluricentricity, Politics and Policies, Routledge, pp.153-162, 2020, 978-0-367-18366-0 ; https://www.routledge.com/The-Soft-Power-of-the-Russian-Language-Pluricentricity-Politics-and-Policies/Mustajoki-Protassova-Yelenevskaya/p/book/9780367183660 (2020)
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Cross-Situational Learning with Reservoir Computing for Language Acquisition Modelling
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In: 2020 International Joint Conference on Neural Networks (IJCNN 2020) ; https://hal.inria.fr/hal-02594725 ; 2020 International Joint Conference on Neural Networks (IJCNN 2020), Jul 2020, Glasgow, Scotland, United Kingdom ; https://wcci2020.org/ (2020)
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Abstract:
International audience ; Understanding the mechanisms enabling children to learn rapidly word-to-meaning mapping through cross-situational learning in uncertain conditions is still a matter of debate. In particular, many models simply look at the word level, and not at the full sentence comprehension level. We present a model of language acquisition, applying cross-situational learning on Recurrent Neural Networks with the Reservoir Computing paradigm. Using the co-occurrences between words and visual perceptions, the model learns to ground a complex sentence, describing a scene involving different objects, into a perceptual representation space. The model processes sentences describing scenes it perceives simultaneously via a simulated vision module: sentences are inputs and simulated vision are target outputs of the RNN. Evaluations of the model show its capacity to extract the semantics of virtually hundred of thousands possible combinations of sentences (based on a context-free grammar); remarkably the model generalises only after a few hundred of partially described scenes via cross-situational learning. Furthermore, it handles polysemous and synonymous words, and deals with complex sentences where word order is crucial for understanding. Finally, further improvements of the model are discussed in order to reach proper reinforced and self-supervised learning schemes, with the goal to enable robots to acquire and ground language by themselves (with no oracle supervision).
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Keyword:
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]; [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]; [SCCO.LING]Cognitive science/Linguistics; [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]; Cross-situational Learning; Echo State Networks; Language Acquisition; Language Learning; Recurrent Neural Networks; Reservoir Computing; Unsupervised Learning
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URL: https://hal.inria.fr/hal-02594725/file/JuvenHinaut2020_IJCNN.pdf https://hal.inria.fr/hal-02594725/document https://hal.inria.fr/hal-02594725
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Electrophysiological investigation of infants' understanding of understanding
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In: ISSN: 1878-9293 ; EISSN: 1878-9307 ; Developmental Cognitive Neuroscience ; https://hal.archives-ouvertes.fr/hal-02868065 ; Developmental Cognitive Neuroscience, Elsevier, 2020, 43, pp.100783. ⟨10.1016/j.dcn.2020.100783⟩ (2020)
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Language Acquisition with Echo State Networks: Towards Unsupervised Learning
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In: ICDL 2020 - IEEE International Conference on Development and Learning ; https://hal.inria.fr/hal-02926613 ; ICDL 2020 - IEEE International Conference on Development and Learning, Oct 2020, Valparaiso / Virtual, Chile (2020)
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Les langues des signes, des langues incarnées
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In: https://halshs.archives-ouvertes.fr/tel-03089705 ; Linguistique. Université Paris8, 2020 (2020)
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An Evaluation of the Celtic Hypothesis for Brythonic Celtic influence on Early English
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The Multilingual Assessment Instrument for Narratives (MAIN): adding Kam to MAIN [Online resource]
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In: New language versions of MAIN: Multilingual Assessment Instrument for Narratives - revised / Natalia Gagarina & Josefin Lindgren (Eds.). Leibniz-Zentrum Allgemeine Sprachwissenschaft: ZAS papers in linguistics ; Nr. 64 (2020), 147-151
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The Multilingual Assessment Instrument for Narratives (MAIN): adding Mandarin to MAIN [Online resource]
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In: New language versions of MAIN: Multilingual Assessment Instrument for Narratives - revised / Natalia Gagarina & Josefin Lindgren (Eds.). Leibniz-Zentrum Allgemeine Sprachwissenschaft: ZAS papers in linguistics ; Nr. 64 (2020), 159-162
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Serbian version of the Multilingual Assessment Instrument for Narratives (MAIN) [Online resource]
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In: New language versions of MAIN: Multilingual Assessment Instrument for Narratives - revised / Natalia Gagarina & Josefin Lindgren (Eds.). Leibniz-Zentrum Allgemeine Sprachwissenschaft: ZAS papers in linguistics ; Nr. 64 (2020), 189-197
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The Multilingual Assessment Instrument for Narratives (MAIN): Adding Cantonese to MAIN [Online resource]
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In: New language versions of MAIN: Multilingual Assessment Instrument for Narratives - revised / Natalia Gagarina & Josefin Lindgren (Eds.). Leibniz-Zentrum Allgemeine Sprachwissenschaft: ZAS papers in linguistics ; Nr. 64 (2020), 23-29
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Polish MAIN: how was it developed and how has it been used so far? [Online resource]
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In: New language versions of MAIN: Multilingual Assessment Instrument for Narratives - revised / Natalia Gagarina & Josefin Lindgren (Eds.). Leibniz-Zentrum Allgemeine Sprachwissenschaft: ZAS papers in linguistics ; Nr. 64 (2020), 169-181
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The adaptation of MAIN to Danish [Online resource]
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In: New language versions of MAIN: Multilingual Assessment Instrument for Narratives - revised / Natalia Gagarina & Josefin Lindgren (Eds.). Leibniz-Zentrum Allgemeine Sprachwissenschaft: ZAS papers in linguistics ; Nr. 64 (2020), 45-50
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MAIN in the Tajik and Shughni languages of Tajikistan [Online resource]
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In: New language versions of MAIN: Multilingual Assessment Instrument for Narratives - revised / Natalia Gagarina & Josefin Lindgren (Eds.). Leibniz-Zentrum Allgemeine Sprachwissenschaft: ZAS papers in linguistics ; Nr. 64 (2020), 235-239
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Adapting the Multilingual Assessment Instrument for Narratives (MAIN) to Catalan [Online resource]
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In: New language versions of MAIN: Multilingual Assessment Instrument for Narratives - revised / Natalia Gagarina & Josefin Lindgren (Eds.). Leibniz-Zentrum Allgemeine Sprachwissenschaft: ZAS papers in linguistics ; Nr. 64 (2020), 31-36
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