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High-Resolution, Non-Invasive Imaging of Upper Vocal Tract Articulators Compatible with Human Brain Recordings

A complete neurobiological understanding of speech motor control requires determination of the relationship between simultaneously recorded neural activity and the kinematics of the lips, jaw, tongue, and larynx. Many speech articulators are internal to the vocal tract, and therefore simultaneously...

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Autores principales: Bouchard, Kristofer E., Conant, David F., Anumanchipalli, Gopala K., Dichter, Benjamin, Chaisanguanthum, Kris S., Johnson, Keith, Chang, Edward F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4809489/
https://www.ncbi.nlm.nih.gov/pubmed/27019106
http://dx.doi.org/10.1371/journal.pone.0151327
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author Bouchard, Kristofer E.
Conant, David F.
Anumanchipalli, Gopala K.
Dichter, Benjamin
Chaisanguanthum, Kris S.
Johnson, Keith
Chang, Edward F.
author_facet Bouchard, Kristofer E.
Conant, David F.
Anumanchipalli, Gopala K.
Dichter, Benjamin
Chaisanguanthum, Kris S.
Johnson, Keith
Chang, Edward F.
author_sort Bouchard, Kristofer E.
collection PubMed
description A complete neurobiological understanding of speech motor control requires determination of the relationship between simultaneously recorded neural activity and the kinematics of the lips, jaw, tongue, and larynx. Many speech articulators are internal to the vocal tract, and therefore simultaneously tracking the kinematics of all articulators is nontrivial—especially in the context of human electrophysiology recordings. Here, we describe a noninvasive, multi-modal imaging system to monitor vocal tract kinematics, demonstrate this system in six speakers during production of nine American English vowels, and provide new analysis of such data. Classification and regression analysis revealed considerable variability in the articulator-to-acoustic relationship across speakers. Non-negative matrix factorization extracted basis sets capturing vocal tract shapes allowing for higher vowel classification accuracy than traditional methods. Statistical speech synthesis generated speech from vocal tract measurements, and we demonstrate perceptual identification. We demonstrate the capacity to predict lip kinematics from ventral sensorimotor cortical activity. These results demonstrate a multi-modal system to non-invasively monitor articulator kinematics during speech production, describe novel analytic methods for relating kinematic data to speech acoustics, and provide the first decoding of speech kinematics from electrocorticography. These advances will be critical for understanding the cortical basis of speech production and the creation of vocal prosthetics.
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spelling pubmed-48094892016-04-05 High-Resolution, Non-Invasive Imaging of Upper Vocal Tract Articulators Compatible with Human Brain Recordings Bouchard, Kristofer E. Conant, David F. Anumanchipalli, Gopala K. Dichter, Benjamin Chaisanguanthum, Kris S. Johnson, Keith Chang, Edward F. PLoS One Research Article A complete neurobiological understanding of speech motor control requires determination of the relationship between simultaneously recorded neural activity and the kinematics of the lips, jaw, tongue, and larynx. Many speech articulators are internal to the vocal tract, and therefore simultaneously tracking the kinematics of all articulators is nontrivial—especially in the context of human electrophysiology recordings. Here, we describe a noninvasive, multi-modal imaging system to monitor vocal tract kinematics, demonstrate this system in six speakers during production of nine American English vowels, and provide new analysis of such data. Classification and regression analysis revealed considerable variability in the articulator-to-acoustic relationship across speakers. Non-negative matrix factorization extracted basis sets capturing vocal tract shapes allowing for higher vowel classification accuracy than traditional methods. Statistical speech synthesis generated speech from vocal tract measurements, and we demonstrate perceptual identification. We demonstrate the capacity to predict lip kinematics from ventral sensorimotor cortical activity. These results demonstrate a multi-modal system to non-invasively monitor articulator kinematics during speech production, describe novel analytic methods for relating kinematic data to speech acoustics, and provide the first decoding of speech kinematics from electrocorticography. These advances will be critical for understanding the cortical basis of speech production and the creation of vocal prosthetics. Public Library of Science 2016-03-28 /pmc/articles/PMC4809489/ /pubmed/27019106 http://dx.doi.org/10.1371/journal.pone.0151327 Text en © 2016 Bouchard et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Bouchard, Kristofer E.
Conant, David F.
Anumanchipalli, Gopala K.
Dichter, Benjamin
Chaisanguanthum, Kris S.
Johnson, Keith
Chang, Edward F.
High-Resolution, Non-Invasive Imaging of Upper Vocal Tract Articulators Compatible with Human Brain Recordings
title High-Resolution, Non-Invasive Imaging of Upper Vocal Tract Articulators Compatible with Human Brain Recordings
title_full High-Resolution, Non-Invasive Imaging of Upper Vocal Tract Articulators Compatible with Human Brain Recordings
title_fullStr High-Resolution, Non-Invasive Imaging of Upper Vocal Tract Articulators Compatible with Human Brain Recordings
title_full_unstemmed High-Resolution, Non-Invasive Imaging of Upper Vocal Tract Articulators Compatible with Human Brain Recordings
title_short High-Resolution, Non-Invasive Imaging of Upper Vocal Tract Articulators Compatible with Human Brain Recordings
title_sort high-resolution, non-invasive imaging of upper vocal tract articulators compatible with human brain recordings
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4809489/
https://www.ncbi.nlm.nih.gov/pubmed/27019106
http://dx.doi.org/10.1371/journal.pone.0151327
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