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1
Towards High-End Scalability on Bio-Inspired Computational Models
In: Computer Science: Faculty Publications and Other Works (2020)
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2
A Computational Theory for the Emergence of Grammatical Categories in Cortical Dynamics ...
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A Computational Theory for the Emergence of Grammatical Categories in Cortical Dynamics ...
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A Computational Theory for the Emergence of Grammatical Categories in Cortical Dynamics ...
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5
neurophon/neurophon: Minor update to ensure future updates include Zenodo author/keyword metadata ...
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neurophon/neurophon: A Computational Theory for the Emergence of Grammatical Categories in Cortical Dynamics ...
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neurophon/neurophon: Prerelease ...
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neurophon/neurophon: A Computational Theory for the Emergence of Grammatical Categories in Cortical Dynamics ...
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9
Neurocomputational cortical memory for spectro-temporal phonetic abstraction.
In: Computer Science: Faculty Publications and Other Works (2019)
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10
Datasets used to train and test the Cortical Spectro-Temporal Model (CSTM). ...
Abstract: ZIP files of folders containing all the datasets (audio file corpora) employed in our research to train the Encoder Layer (EL) and the SVMs and to test the complete CSTM. This folder includes a set of 840 corpora which are distributed in 2 corpora for each configuration organized by 2 sets of synthesized voices, 3 syllabic conditions (i.e. mono-, di- and tri-syllabic English words) and 10 completely different vocabularies all distributed in 6 acoustic variants, beyond the original version of the corpora. The 6 acoustic variants corresponds to: two levels of white noise (19.8 dB and 13.8 dB Signal to Noise Ratio (SNR) average Root Mean Square (RMS) power rate), two levels of reverberation (Reveberation-Time 60 dB (RT-60) value of 0.61 seconds and 1.78 seconds) and variations of pitch on both directions (from E to G and from E to C). ...
Keyword: Cortical dynamics, Early language acquisition, Incidental phonetic acquisition, Sparse Distributed Representations, Unsupervised Learning, Biologically Inspired Computational Models, Neural Networks, Cortical Columnar Organization
URL: https://dx.doi.org/10.5281/zenodo.2576130
https://zenodo.org/record/2576130
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11
Datasets used to train and test the Cortical Spectro-Temporal Model (CSTM). ...
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