Ken Steven's focus on speech production and our development of the speech inversion system

Throughout his highly distinguished career, Ken Stevens studied how the relationship between the constrictions used in speech production result in the acoustic properties of the speech signal. Ken’s pioneering rate in articulation stemming from the X-ray study he participated in and studies by his students in the timing and movement of articulatory gestures played a pivotal role in our work to develop a Speech Inversion (SI) system. The SI system, using deep learning, initially used ground-truth information obtained from the Wisconsin X-ray Microbeam database to estimate the articulatory trajectories for the lips, tongue tip, and tongue dorsum. Adding glottal information based on an aperiodicity/periodicity/pitch detector resulted in a significant improvement in the correlation between estimated and ground truth data. More recently, we added ground truth articulatory data about the velopharyngeal port constriction, using both nasometry and the novel technique of high-speed nasopharyngoscopy. In this talk, I will discuss the SI system and its ability to help us understand how speech production changes as a result of mental state, speech disorder, speaking rate, and accent.

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Publication Details

Journal
The Journal of the Acoustical Society of America
Published
2024-10-01
DOI
https://doi.org/10.1121/10.0035169
Citations
1
Primary Topic
Speech Recognition and Synthesis
Type
article
Field-Weighted Citation Impact
0.35
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Ken Steven's focus on speech production and our development of the speech inversion system

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The Journal of the Acoustical Society of America
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article

Ken Steven's focus on speech production and our development of the speech inversion system

Liran Oren, Mark Tiede, Suzanne Boyce, Yashish M. Siriwardena, Carol Espy-Wilson
article en
1 citations

Abstract

Throughout his highly distinguished career, Ken Stevens studied how the relationship between the constrictions used in speech production result in the acoustic properties of the speech signal. Ken’s pioneering rate in articulation stemming from the X-ray study he participated in and studies by his students in the timing and movement of articulatory gestures played a pivotal role in our work to develop a Speech Inversion (SI) system. The SI system, using deep learning, initially used ground-truth information obtained from the Wisconsin X-ray Microbeam database to estimate the articulatory trajectories for the lips, tongue tip, and tongue dorsum. Adding glottal information based on an aperiodicity/periodicity/pitch detector resulted in a significant improvement in the correlation between estimated and ground truth data. More recently, we added ground truth articulatory data about the velopharyngeal port constriction, using both nasometry and the novel technique of high-speed nasopharyngoscopy. In this talk, I will discuss the SI system and its ability to help us understand how speech production changes as a result of mental state, speech disorder, speaking rate, and accent.

The Journal of the Acoustical Society of AmericaVol. 156(4_Supplement)
Haskins Laboratories (US), University of Cincinnati (US), University of Maryland, College Park (US)
Openalex Percentile: Top 30%
Speech Recognition and Synthesis
0.35
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Ken Steven's focus on speech production and our development of the speech inversion system — Liran Oren, Mark Tiede, et al. · The Journal of the Acoustical Society of America (2024) | TGRS Research Map | TGRS