Journal article
A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images
Scientific data, Vol.8(1), pp.187-187
02/15/2021
DOI: 10.1038/s41597-021-00976-x
PMID: 34285240
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 subjects performing linguistically motivated speech
tasks, alongside the corresponding first-ever 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 subject.
Details
- Title: Subtitle
- A multispeaker dataset of raw and reconstructed speech production real-time MRI video and 3D volumetric images
- Creators
- Yongwan LimAsterios ToutiosYannick BliesenerYe TianSajan Goud LingalaColin VazTanner SorensenMiran OhSarah HarperWeiyi ChenYoonjeong LeeJohannes TögerMairym Lloréns MontesserinCaitlin SmithBianca GodinezLouis GoldsteinDani ByrdKrishna S Nayak - University of Southern CaliforniaShrikanth S Narayanan
- Resource Type
- Journal article
- Publication Details
- Scientific data, Vol.8(1), pp.187-187
- DOI
- 10.1038/s41597-021-00976-x
- PMID
- 34285240
- NLM abbreviation
- Sci Data
- ISSN
- 2052-4463
- eISSN
- 2052-4463
- Grant note
- DOI: 10.13039/100000001, name: National Science Foundation, award: 1908865
- Language
- English
- Date published
- 02/15/2021
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology
- Record Identifier
- 9984196995202771
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