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1
Where do successful populations originate from?
Andras, Peter; Stanton, Adam. - : Elsevier, 2021
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2
Modelowanie percepcji transformacji politycznej. Podejście systemowe ...
Kasianiuk, Krzysztof. - : figshare, 2021
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3
Modelowanie percepcji transformacji politycznej. Podejście systemowe ...
Kasianiuk, Krzysztof. - : figshare, 2021
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4
Computation of transition matrices.pptx ...
Gagniuc, Paul. - : figshare, 2021
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5
Computation of transition matrices.pptx ...
Gagniuc, Paul. - : figshare, 2021
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6
Finetuning Pretrained Transformers into Variational Autoencoders ...
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7
How the input shapes the acquisition of verb morphology: elicited production and computational modelling in two highly inflected languages ...
Engelmann, Felix. - : Open Science Framework, 2021
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8
Language policy and planning: a discussion on the complexity of language matters and the role of computational methods
In: ISSN: 2662-9283 ; SN Social Sciences, Vol. 1, No 8 (2021) (2021)
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9
Tattoos as a window onto cross-linguistic differences in scalar implicature
In: Experiments in Linguistic Meaning; Vol 1 (2021); 147-158 ; 2694-1791 (2021)
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10
Cultural evolution of scalar categorization: how cognition and communication affect the structure of categories on scalar conceptual domains ...
Carcassi, Fausto. - : The University of Edinburgh, 2020
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11
Complexity Theory: Applications to Language Policy and Planning
Civico, Marco. - : Université de Genève, 2020
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12
Combining predictive coding and neural oscillations enables online syllable recognition in natural speech
In: ISSN: 2041-1723 ; Nature Communications, Vol. 11, No 1 (2020) P. 3117 (2020)
Abstract: On-line comprehension of natural speech requires segmenting the acoustic stream into discrete linguistic elements. This process is argued to rely on theta-gamma oscillation coupling, which can parse syllables and encode them in decipherable neural activity. Speech comprehension also strongly depends on contextual cues that help predicting speech structure and content. To explore the effects of theta-gamma coupling on bottom-up/top-down dynamics during on-line syllable identification, we designed a computational model (Precoss—predictive coding and oscillations for speech) that can recognise syllable sequences in continuous speech. The model uses predictions from internal spectro-temporal representations of syllables and theta oscillations to signal syllable onsets and duration. Syllable recognition is best when theta-gamma coupling is used to temporally align spectro-temporal predictions with the acoustic input. This neurocomputational modelling work demonstrates that the notions of predictive coding and neural oscillations can be brought together to account for on-line dynamic sensory processing.
Keyword: Computational modelling; info:eu-repo/classification/ddc/616.8; Neural oscillations; Neural theory; Predictive coding; Speech processing
URL: https://archive-ouverte.unige.ch/unige:143429
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13
Computational modelling of an auditory lexical decision experiment using jTRACE and TISK
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14
Computational Modelling of Spoken Word Recognition in the Auditory Lexical Decision Task
Nenadić, Filip. - : University of Alberta. Department of Linguistics., 2020
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15
Cultural evolution of scalar categorization: how cognition and communication affect the structure of categories on scalar conceptual domains
Carcassi, Fausto. - : The University of Edinburgh, 2020
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16
Defining distinctiveness: A computational and experimental analysis
Spear, Jackie. - 2020
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17
Modelling the Semantic Change Dynamics using Diachronic Word Embedding
In: 11th International Conference on Agents and Artificial Intelligence (NLPinAI Special Session) ; https://hal.archives-ouvertes.fr/hal-02048377 ; 11th International Conference on Agents and Artificial Intelligence (NLPinAI Special Session), Feb 2019, Prague, Czech Republic (2019)
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18
Understanding Semantic Implicit Learning through distributional linguistic patterns: A computational perspective ...
Alikaniotis, Dimitrios. - : Apollo - University of Cambridge Repository, 2019
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19
Neurobiology of incremental speech comprehension
Choi, Hun Seok. - : University of Cambridge, 2019. : Psychology, 2019. : Clare, 2019
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20
Understanding Semantic Implicit Learning through distributional linguistic patterns: A computational perspective
Alikaniotis, Dimitrios. - : University of Cambridge, 2019. : Downing, 2019
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