We introduce the first-ever public domain real-time MRI raw dataset for the study of human speech production. The dataset consists of raw, multi-receiver-coil MRI data with non-Cartesian, spiral sampling trajectory and reconstructed images derived using a reference reconstruction method along with synchronized audio for 72 subjects performing 32 linguistically motivated speech tasks. This dataset can be used to develop traditional and machine learning / artificial intelligence approaches for dynamic image reconstruction in the context of fast aperiodic motion, which is currently an unsolved problem, as well as for artifact correction, feature extraction, and direct extraction of linguistically relevant biomarkers.
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