The long term goals of this project are to wed state-of-the-art technology for imaging the vocal tract with a linguistically informed analysis of the speech tasks or goals requisite in the production of spoken language. Our team has developed an approach for MRI image reconstruction rates of 24 images per second, making veridical real-time movies of speech production possible for the first time without X-rays (Narayanan, Nayak, Lee Sethy, & Byrd, in press). Data show clear real-time movements of the lips, tongue, and velum, providing us exquisite information about the spatiotemporal properties of speech gestures in both the oral and pharyngeal portions of the vocal tract. Our long-term goal is to understand the aspects of vocal tract shaping that are critically controlled during speech, both for sounds known to be complex in geometry (e.g.,/r/ & sibilant fricatives) and for sounds known to be complex in their temporal structuring (e.g.,/I/ & diphthongs). An understanding of vocal tract shape as a fundamentally dynamic aspect of linguistic organization will do much to add to the field's current--basically static (i.e., postural & fixed time-point)--approach to describing the production of speech.
The specific aims of this proposal are to further develop the technology and analysis platform of real-time MRI, which provides the scaffolding for the project, while pursuing production studies in three areas: sounds thought to have sequential vocal tract constriction goals, sounds with prosodically-sensitive coordination of vocal tract constriction goals, and sounds with geometrically complex vocal tract shaping goals. An appropriate understanding of how these sounds are produced in space and time is fundamentally a phonological question in that it bears directly on the phonological representation of segmental units, a representation that we take to be intrinsically articulatory and dynamic.
| Lim, Yongwan; Zhu, Yinghua; Lingala, Sajan Goud et al. (2018) 3D dynamic MRI of the vocal tract during natural speech. Magn Reson Med : |
| Lammert, Adam C; Shadle, Christine H; Narayanan, Shrikanth S et al. (2018) Speed-accuracy tradeoffs in human speech production. PLoS One 13:e0202180 |
| Vaz, Colin; Ramanarayanan, Vikram; Narayanan, Shrikanth (2018) Acoustic Denoising using Dictionary Learning with Spectral and Temporal Regularization. IEEE/ACM Trans Audio Speech Lang Process 26:967-980 |
| Parrell, Benjamin; Narayanan, Shrikanth (2018) Explaining Coronal Reduction: Prosodic Structure and Articulatory Posture. Phonetica 75:151-181 |
| Gupta, Rahul; Audhkhasi, Kartik; Jacokes, Zach et al. (2018) Modeling multiple time series annotations as noisy distortions of the ground truth: An Expectation-Maximization approach. IEEE Trans Affect Comput 9:76-89 |
| Lingala, Sajan Goud; Zhu, Yinghua; Lim, Yongwan et al. (2017) Feasibility of through-time spiral generalized autocalibrating partial parallel acquisition for low latency accelerated real-time MRI of speech. Magn Reson Med 78:2275-2282 |
| Hagedorn, Christina; Proctor, Michael; Goldstein, Louis et al. (2017) Characterizing Articulation in Apraxic Speech Using Real-Time Magnetic Resonance Imaging. J Speech Lang Hear Res 60:877-891 |
| Töger, Johannes; Sorensen, Tanner; Somandepalli, Krishna et al. (2017) Test-retest repeatability of human speech biomarkers from static and real-time dynamic magnetic resonance imaging. J Acoust Soc Am 141:3323 |
| Lingala, Sajan Goud; Zhu, Yinghua; Kim, Yoon-Chul et al. (2017) A fast and flexible MRI system for the study of dynamic vocal tract shaping. Magn Reson Med 77:112-125 |
| Lingala, Sajan Goud; Sutton, Brad P; Miquel, Marc E et al. (2016) Recommendations for real-time speech MRI. J Magn Reson Imaging 43:28-44 |
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