Dynamics of plosive consonants via imaging, computations, and soft electronics

Author:

Kim Jin-Tae1ORCID,Ouyang Wei1ORCID,Hwang Hanul2,Jeong Hyoyoung13ORCID,Kang Soohyeon4,Bose Sanjeeb25ORCID,Kwak Sung Soo16,Ni Xiaoyue7ORCID,Kim Hyeonsu8,Park Jaehong8ORCID,Chen Hope9,Soetikno Alan9,Kim Joohee1,Xu Shuai9,Chamorro Leonardo P.4ORCID,Rogers John A.1

Affiliation:

1. Querrey Simpson Institute for Bioelectronics, Northwestern University, Evanston, IL 60208

2. Center for Turbulence Research, Stanford University, Stanford, CA 94305

3. Department of Electrical and Computer Engineering, University of California - Davis, Davis, CA 95616

4. Department of Mechanical Science and Engineering, University of Illinois, Urbana, IL 61801

5. Cascade Technologies Inc., Palo Alto, CA 94303

6. Bionics Research Center of Biomedical Research Institute, Korea Institute of Science and Technology, Seoul 02792, Republic of Korea

7. Department of Mechanical Engineering and Materials Science, Pratt School of Engineering, Duke University, Durham, NC 27708

8. Department of Chemical and Biomolecular Engineering, University of Illinois, Urbana, IL 61801

9. Department of Dermatology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611

Abstract

A quantitative understanding of the coupled dynamics of flow and particles in aerosol and droplet transmission associated with speech remains elusive. Here, we summarize an effort that integrates insights into flow-particle dynamics induced by the production plosive sounds during speech with skin-integrated electronic systems for monitoring the production of these sounds. In particular, we uncover diffusive and ballistic regimes separated by a threshold particle size and characterize the Lagrangian acceleration and pair dispersion. Lagrangian dynamics of the particles in the diffusive regime exhibit features of isotropic turbulence. These fundamental findings highlight the value in skin-interfaced wireless sensors for continuously measuring critical speech patterns in clinical settings, work environments, and the home, based on unique neck biomechanics associated with the generation of plosive sounds. We introduce a wireless, soft device that captures these motions to enable detection of plosive sounds in multiple languages through a convolutional neural network approach. This work spans fundamental flow-particle physics to soft electronic technology, with implications in monitoring and studying critical speech patterns associated with aerosol and droplet transmissions relevant to the spread of infectious diseases.

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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