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 English. Electromagnetic articulography data have also been presently collected from four of these speakers. The two modalities were recorded in two independent sessions while the subjects produced the same 460 sentence corpus used previously in the MOCHA-TIMIT database. In both cases the audio signal was recorded and synchronized with the articulatory data. The database and companion software are freely available to the research community.
This letter describes a data acquisition setup for recording, and processing, running speech from a person in a magnetic resonance imaging (MRI) scanner. The main focus is on ensuring synchronicity between image and audio acquisition, and in obtaining good signal to noise ratio to facilitate further speech analysis and modeling. A field-programmable gate array based hardware design for synchronizing the scanner image acquisition to other external data such as audio is described. The audio setup itself features two fiber optical microphones and a noise-canceling filter. Two noise cancellation methods are described including a novel approach using a pulse sequence specific model of the gradient noise of the MRI scanner. The setup is useful for scientific speech production studies. Sample results of speech and singing data acquired and processed using the proposed method are given.
We describe a method for unsupervised region segmentation of an image using its spatial frequency domain representation. The algorithm was designed to process large sequences of real-time magnetic resonance (MR) images containing the 2-D midsagittal view of a human vocal tract airway. The segmentation algorithm uses an anatomically informed object model, whose fit to the observed image data is hierarchically optimized using a gradient descent procedure. The goal of the algorithm is to automatically extract the time-varying vocal tract outline and the position of the articulators to facilitate the study of the shaping of the vocal tract during speech production.
The coordination of velum and oral gestures for English [n] is studied using real-time MRI movies to reconstruct vocal tract aperture functions. This technique allows for the examination of parts of the vocal tract otherwise inaccessible to dynamic imaging or movement tracking. The present experiment considers syllable onset, coda, and juncture geminate nasals and also addresses the effects of a variety of word stress patterns on segment internal coordination. We find a bimodal timing pattern in which near-synchrony of velum lowering and tongue tip raising characterizes the timing for onsets and temporal lag between the gestures is characteristic for codas, supporting and extending the findings of Krakow (1989Krakow ( ), 1993 for [m]. Intervocalic word-internal nasals are found to have timing patterns that are sensitive to the local stress context, which suggests the presence of an underlying timing specification that can yield flexibly.
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