Michael I. Proctor

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USC-TIMIT is an extensive database of multimodal speech production data, developed to complement existing resources available to the speech research community and with the intention of being continuously refined and augmented. The database currently includes real-time magnetic resonance imaging data from five male and five female speakers of American(More)
We present MRI-TIMIT: a large-scale database of synchronized audio and real-time magnetic resonance imaging (rtMRI) data for speech research. The database currently consists of speech data acquired from two male and two female speakers of American English. Subjects’ upper airways were imaged in the midsagittal plane while reading the same 460 sentence(More)
Due to its aerodynamic, articulatory, and acoustic complexities, the fricative /s/ is known to require high precision in its control, and to be highly resistant to coarticulation. This study documents in detail how jaw, tongue front, tongue back, lips, and the first spectral moment covary during the production of /s/, to establish how coarticulation affects(More)
A method of rapid semi-automatic segmentation of real-time magnetic resonance image data for parametric analysis of vocal tract shaping is described. Tissue boundaries are identified by seeking pixel intensity thresholds along tract-normal gridlines. Airway contours are constrained with respect to a tract centerline defined as an optimal path over the graph(More)
We explore robust methods of automatically quantifying constriction location, constriction degree and gestural kinematics of Italian short and long consonants using direct image analysis techniques applied to rtMRI data. Articulatory kinematics are estimated from correlated regional changes in pixel intensity. We demonstrate that these methods are capable(More)
A method of rapid, automatic extraction of consonantal articulatory trajectories from real-time magnetic resonance image sequences is described. Constriction location targets are estimated by identifying regions of maximally-dynamic correlated pixel activity along the palate, the alveolar ridge, and at the lips. Tissue movement into and out of the(More)
In order to fully understand inter-speaker variability in the acoustical and articulatory domains, morphological variability must be considered, as well. Human vocal tracts display substantial morphological differences, all of which have the potential to impact a speaker’s acoustic output. The palate and rear pharyngeal wall, in particular, vary widely and(More)
Vocal tract area function estimation from three-dimensional (3D) volumetric dataset often involves complex and manual procedures such as oblique slice cutting and image segmentation. We introduce a semi-automatic method for estimating vocal tract area function from 3D Magnetic Resonance Imaging (MRI) datasets. The method was implemented on a custom MATLAB(More)
We explore the use of real-time magnetic resonance imaging (rtMRI) as a tool to investigate apraxic speech, in particular, by examining articulatory behavior. Our pilot data reveal that covert (silent) gestural intrusion errors (employing an intrinsically simple 1:1 mode of coupling) are made more frequently by an apraxic subject than by fluent speakers.(More)
PURPOSE Adult human vocal tracts display considerable morphological variation across individuals, but the nature and extent of this variation has not been extensively studied for many vocal tract structures. There exists a need to analyze morphological variation and, even more basically, to develop a methodology for morphological analysis of the vocal(More)