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1
Kurmanji Stemmer ...
Rahimi, Adel. - : Zenodo, 2015
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2
Pyconcordancer ...
Rahimi, Adel. - : Zenodo, 2015
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3
Kurmanji Stemmer ...
Rahimi, Adel. - : Zenodo, 2015
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4
Data from: A Convolution Kernel Approach to Identifying Comparisons in Text ...
TKACHENKO Hady W. LAUW Maksim. - : SMU Research Data Repository (RDR), 2015
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5
Data from: A Convolution Kernel Approach to Identifying Comparisons in Text ...
TKACHENKO Hady W. LAUW Maksim. - : SMU Research Data Repository (RDR), 2015
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6
BabbleModelParameterVariationsSounds ...
Warlaumont, Anne. - : figshare, 2015
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7
Babble Model Parameter Variations Sounds ...
Warlaumont, Anne. - : figshare, 2015
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8
Babble Model Parameter Variations Sounds ...
Warlaumont, Anne. - : figshare, 2015
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9
Babble Model Parameter Variations Sounds ...
Warlaumont, Anne. - : figshare, 2015
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10
Babble Model Parameter Variations Sounds ...
Warlaumont, Anne. - : figshare, 2015
Abstract: These sounds were produced by a computational spiking neural network model of learning to produce syllabic vocalizations (i.e. canonical babbling) in infancy. The vocalizations produced by each simulation from each parameter combination were sampled at regular intervals. For each simulation, these samples were concatenated into a single sound file that can provide an auditory sense of how the simulation's vocalizations changed over time. The best parameter combination is 200 neurons (200n) and 2 muscle scaling (2n). ...
Keyword: Artificial Intelligence and Image Processing; Computational Biology; Developmental and Educational Psychology; FOS Computer and information sciences; FOS Languages and literature; Linguistics; Neuroscience; Neuroscience and Physiological Psychology
URL: https://figshare.com/articles/dataset/BabbleModelParameterVariationsSounds/1486454/2
https://dx.doi.org/10.6084/m9.figshare.1486454.v2
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11
Babble Model Parameter Variations Sounds ...
Warlaumont, Anne. - : figshare, 2015
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12
The balance of scalar implicature ...
Tavano, Erin M.. - : University of Southern California Digital Library (USC.DL), 2015
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