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A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images
Real-time magnetic resonance imaging (RT-MRI) of human speech production is enabling significant advances in speech science, linguistics, bio-inspired speech technology development, and clinical applications. Easy access to RT-MRI is however limited, and comprehensive datasets with broad access are...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8292336/ https://www.ncbi.nlm.nih.gov/pubmed/34285240 http://dx.doi.org/10.1038/s41597-021-00976-x |
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author | Lim, Yongwan Toutios, Asterios Bliesener, Yannick Tian, Ye Lingala, Sajan Goud Vaz, Colin Sorensen, Tanner Oh, Miran Harper, Sarah Chen, Weiyi Lee, Yoonjeong Töger, Johannes Monteserin, Mairym Lloréns Smith, Caitlin Godinez, Bianca Goldstein, Louis Byrd, Dani Nayak, Krishna S. Narayanan, Shrikanth S. |
author_facet | Lim, Yongwan Toutios, Asterios Bliesener, Yannick Tian, Ye Lingala, Sajan Goud Vaz, Colin Sorensen, Tanner Oh, Miran Harper, Sarah Chen, Weiyi Lee, Yoonjeong Töger, Johannes Monteserin, Mairym Lloréns Smith, Caitlin Godinez, Bianca Goldstein, Louis Byrd, Dani Nayak, Krishna S. Narayanan, Shrikanth S. |
author_sort | Lim, Yongwan |
collection | PubMed |
description | Real-time magnetic resonance imaging (RT-MRI) of human speech production is enabling significant advances in speech science, linguistics, bio-inspired speech technology development, and clinical applications. Easy access to RT-MRI is however limited, and comprehensive datasets with broad access are needed to catalyze research across numerous domains. The imaging of the rapidly moving articulators and dynamic airway shaping during speech demands high spatio-temporal resolution and robust reconstruction methods. Further, while reconstructed images have been published, to-date there is no open dataset providing raw multi-coil RT-MRI data from an optimized speech production experimental setup. Such datasets could enable new and improved methods for dynamic image reconstruction, artifact correction, feature extraction, and direct extraction of linguistically-relevant biomarkers. The present dataset offers a unique corpus of 2D sagittal-view RT-MRI videos along with synchronized audio for 75 participants performing linguistically motivated speech tasks, alongside the corresponding public domain raw RT-MRI data. The dataset also includes 3D volumetric vocal tract MRI during sustained speech sounds and high-resolution static anatomical T2-weighted upper airway MRI for each participant. |
format | Online Article Text |
id | pubmed-8292336 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-82923362021-07-23 A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images Lim, Yongwan Toutios, Asterios Bliesener, Yannick Tian, Ye Lingala, Sajan Goud Vaz, Colin Sorensen, Tanner Oh, Miran Harper, Sarah Chen, Weiyi Lee, Yoonjeong Töger, Johannes Monteserin, Mairym Lloréns Smith, Caitlin Godinez, Bianca Goldstein, Louis Byrd, Dani Nayak, Krishna S. Narayanan, Shrikanth S. Sci Data Data Descriptor Real-time magnetic resonance imaging (RT-MRI) of human speech production is enabling significant advances in speech science, linguistics, bio-inspired speech technology development, and clinical applications. Easy access to RT-MRI is however limited, and comprehensive datasets with broad access are needed to catalyze research across numerous domains. The imaging of the rapidly moving articulators and dynamic airway shaping during speech demands high spatio-temporal resolution and robust reconstruction methods. Further, while reconstructed images have been published, to-date there is no open dataset providing raw multi-coil RT-MRI data from an optimized speech production experimental setup. Such datasets could enable new and improved methods for dynamic image reconstruction, artifact correction, feature extraction, and direct extraction of linguistically-relevant biomarkers. The present dataset offers a unique corpus of 2D sagittal-view RT-MRI videos along with synchronized audio for 75 participants performing linguistically motivated speech tasks, alongside the corresponding public domain raw RT-MRI data. The dataset also includes 3D volumetric vocal tract MRI during sustained speech sounds and high-resolution static anatomical T2-weighted upper airway MRI for each participant. Nature Publishing Group UK 2021-07-20 /pmc/articles/PMC8292336/ /pubmed/34285240 http://dx.doi.org/10.1038/s41597-021-00976-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Lim, Yongwan Toutios, Asterios Bliesener, Yannick Tian, Ye Lingala, Sajan Goud Vaz, Colin Sorensen, Tanner Oh, Miran Harper, Sarah Chen, Weiyi Lee, Yoonjeong Töger, Johannes Monteserin, Mairym Lloréns Smith, Caitlin Godinez, Bianca Goldstein, Louis Byrd, Dani Nayak, Krishna S. Narayanan, Shrikanth S. A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images |
title | A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images |
title_full | A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images |
title_fullStr | A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images |
title_full_unstemmed | A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images |
title_short | A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images |
title_sort | multispeaker dataset of raw and reconstructed speech production real-time mri video and 3d volumetric images |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8292336/ https://www.ncbi.nlm.nih.gov/pubmed/34285240 http://dx.doi.org/10.1038/s41597-021-00976-x |
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