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1
Low-dimensional representation of infant and adult vocalization acoustics ...
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2
Multimodal Dynamics of Extended Communication
Alviar Guzman, Maria Camila. - : eScholarship, University of California, 2021
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3
Additional Results and details of "On the physical origin of linguistic laws and lognormality in speech" ...
Torre, Iván G.; Luque, Bartolo; Lacasa, Lucas. - : The Royal Society, 2019
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4
Additional Results and details of "On the physical origin of linguistic laws and lognormality in speech" ...
Torre, Iván G.; Luque, Bartolo; Lacasa, Lucas. - : The Royal Society, 2019
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5
Supplementary material from "On the physical origin of linguistic laws and lognormality in speech" ...
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6
Supplementary material from "On the physical origin of linguistic laws and lognormality in speech" ...
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7
On the physical origin of linguistic laws and lognormality in speech
Torre, Iván G.; Luque, Bartolo; Lacasa, Lucas. - : The Royal Society, 2019
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8
A neural network model of the articulatory-acoustic forward mapping trained on recordings of articulatory parameters. ...
Kello, Christopher T.; Plaut, David. - : Figshare, 2018
Abstract: Three neural network models were trained on the forward mapping from articulatory positions to acoustic outputs for a single speaker of the Edinburgh multi-channel articulatory speech database. The model parameters (i.e., connection weights) were learned via the backpropagation of error signals generated by the difference between acoustic outputs of the models, and their acoustic targets. Efficacy of the trained models was assessed by subjecting the models' acoustic outputs to speech intelligibility tests. The results of these tests showed that enough phonetic information was captured by the models to support rates of word identification as high as 84%, approaching an identification rate of 92% for the actual target stimuli. These forward models could serve as one component of a data-driven articulatory synthesizer. The models also provide the first step toward building a model of spoken word acquisition and phonological development trained on real speech. ...
Keyword: 170199 Psychology not elsewhere classified; FOS Psychology
URL: https://figshare.com/articles/A_neural_network_model_of_the_articulatory-acoustic_forward_mapping_trained_on_recordings_of_articulatory_parameters_/6613178/1
https://dx.doi.org/10.1184/r1/6613178.v1
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9
Supplementary material from "Hierarchical temporal structure in music, speech and animal vocalizations: jazz is like a conversation, humpbacks sing like hermit thrushes" ...
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10
Supplementary material from "Hierarchical temporal structure in music, speech and animal vocalizations: jazz is like a conversation, humpbacks sing like hermit thrushes" ...
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11
Hierarchical temporal structure in music, speech and animal vocalizations: jazz is like a conversation, humpbacks sing like hermit thrushes
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12
The segment as the minimal planning unit in speech production and reading aloud: evidence and implications.
Liu, Qiang; Kello, Christopher T; Kawamoto, Alan H. - : eScholarship, University of California, 2015
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13
The segment as the minimal planning unit in speech production and reading aloud: evidence and implications
Kawamoto, Alan H.; Liu, Qiang; Kello, Christopher T.. - : Frontiers Media S.A., 2015
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14
Walking across Wikipedia: a scale-free network model of semantic memory retrieval.
In: Frontiers in psychology, vol 5, iss FEB (2014)
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15
Walking across Wikipedia: a scale-free network model of semantic memory retrieval
Thompson, Graham W.; Kello, Christopher T.. - : Frontiers Media S.A., 2014
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16
Intrinsic fluctuations yield pervasive 1/f scaling: comment on Moscoso del Prado Martín (2011)
In: Cognitive science. - Hoboken, NJ : Wiley-Blackwell 35 (2011) 5, 838-841
BLLDB
OLC Linguistik
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17
Learning orthographic and phonological representations in models of monosyllabic and bisyllabic naming
In: The European journal of cognitive psychology. - Basingstoke : Psychology Press 22 (2010) 5, 650-668
BLLDB
OLC Linguistik
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18
Scaling laws in cognitive sciences
Kello, Christopher T.; Brown, G. D. A. (Gordon D. A.); Ferrer-i-Cancho, Ramon. - : Elsevier Science London, 2010
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19
Sequence Encoders Enable Large‐Scale Lexical Modeling: Reply to Bowers and Davis (2009)
In: Cognitive science. - Hoboken, NJ : Wiley-Blackwell 33 (2009) 7, 1187-1191
OLC Linguistik
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20
Sequence encoders enable large-scale lexical modeling: reply to Bowers and Davis (2009)
In: Cognitive science. - Hoboken, NJ : Wiley-Blackwell 33 (2009) 7, 1187-1191
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