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A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images.

Authors :
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.
Source :
Scientific Data; 7/20/2021, Vol. 8 Issue 1, p1-14, 14p
Publication Year :
2021

Abstract

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. Measurement(s) Speech • vocal tract Technology Type(s) magnetic resonance imaging Factor Type(s) age • sex • native/non-native speaker Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14892921 [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20524463
Volume :
8
Issue :
1
Database :
Complementary Index
Journal :
Scientific Data
Publication Type :
Academic Journal
Accession number :
151507713
Full Text :
https://doi.org/10.1038/s41597-021-00976-x