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1
Deep Neural Convolutive Matrix Factorization for Articulatory Representation Decomposition ...
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2
A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images ...
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3
A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images ...
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4
A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images ...
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5
Complexity patterns underlying speech production activity
In: ISSP 2020 ; https://hal.archives-ouvertes.fr/hal-03100430 ; ISSP 2020, Dec 2020, Online, United States (2020)
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6
Derivation of Fitts' law from the Task Dynamics model of speech production ...
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7
Variability in individual constriction contributions to third formant values in American English /ɹ/a)
In: J Acoust Soc Am (2020)
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8
How an aglossic speaker produces an alveolar-like percept without a functional tongue tip
In: J Acoust Soc Am (2020)
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9
Engineering In Speech Science (Hagedorn et al., 2019) ...
Abstract: Purpose: As increasing amounts and types of speech data become accessible, health care and technology industries increasingly demand quantitative insight into speech content.The potential for speech data to provide insight into cognitive, affective, and psychological health states and behavior crucially depends on the ability to integrate speech data into the scientific process. Current engineering methods for acquiring, analyzing, and modeling speech data present the opportunity to integrate speech data into the scientific process. Additionally, machine learning systems recognize patterns in data that can facilitate hypothesis generation, data analysis, and statistical modeling. The goals of the present article are (a) to review developments across these domains that have allowed real-time magnetic resonance imaging to shed light on aspects of atypical speech articulation; (b) in a parallel vein, to discuss how advancements in signal processing have allowed for an improved understanding of communication ...
Keyword: 170204 Linguistic Processes incl. Speech Production and Comprehension; FOS Psychology; Language
URL: https://asha.figshare.com/articles/Engineering_In_Speech_Science_Hagedorn_et_al_2019_/7740191
https://dx.doi.org/10.23641/asha.7740191
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Engineering In Speech Science (Hagedorn et al., 2019) ...
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11
Noggin Nodding: Head Movement Correlates With Increased Effort in Accelerating Speech Production Tasks
Tiede, Mark; Goldstein, Louis; Mooshammer, Christine. - : Humboldt-Universität zu Berlin, 2019
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12
Noggin Nodding: Head Movement Correlates With Increased Effort in Accelerating Speech Production Tasks ...
Tiede, Mark; Mooshammer, Christine; Goldstein, Louis. - : Humboldt-Universität zu Berlin, 2019
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13
The Role of Temporal Modulation in Sensorimotor Interaction
Goldstein, Louis. - : Frontiers Media S.A., 2019
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14
Noggin Nodding: Head Movement Correlates With Increased Effort in Accelerating Speech Production Tasks
Tiede, Mark; Mooshammer, Christine; Goldstein, Louis. - : Frontiers Media S.A., 2019
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15
Task-dependence of articulator synergiesa)
Sorensen, Tanner; Toutios, Asterios; Goldstein, Louis. - : Acoustical Society of America, 2019
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16
Towards the Quantification of Peggy Babcock: Speech Errors and Their Position within the Word
Mooshammer, Christine [Verfasser]; Tiede, Mark [Verfasser]; Shattuck-Hufnagel, Stefanie [Verfasser]. - Berlin : Humboldt-Universität zu Berlin, 2018
DNB Subject Category Language
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17
Speech inversion using naturally spoken data
In: Rethinking reduction (2018), S. 243-276
Leibniz-Zentrum Allgemeine Sprachwissenschaft
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18
Towards the Quantification of Peggy Babcock: Speech Errors and Their Position within the Word
Mooshammer, Christine; Tiede, Mark; Shattuck-Hufnagel, Stefanie. - : Humboldt-Universität zu Berlin, 2018
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19
Towards the Quantification of Peggy Babcock: Speech Errors and Their Position within the Word ...
Mooshammer, Christine; Tiede, Mark; Shattuck-Hufnagel, Stefanie. - : Humboldt-Universität zu Berlin, 2018
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20
Quantitative Analysis of Multimodal Speech Data
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