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RFID Tattoo: A Wireless Platform for Speech Recognition

Authors:

Swarun KumarAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 3, Issue 4

Article No.: 155, Pages 1 - 24

https://doi.org/10.1145/3369812

Published: 14 September 2020 Publication History

Abstract

This paper presents an RF-based assistive technology for voice impairments (i.e., dysphonia), which occurs in an estimated 1% of the global population. We specifically focus on acquired voice disorders where users continue to be able to make facial and lip gestures associated with speech. Despite the rich literature on assistive technologies in this space, there remains a gap for a solution that neither requires external infrastructure in the environment, battery-powered sensors on skin or body-worn manual input devices.

We present RFTattoo, which to our knowledge is the first wireless speech recognition system for voice impairments using batteryless and flexible RFID tattoos. We design specialized wafer-thin tattoos attached around the user's face and easily hidden by makeup. We build models that process signal variations from these tattoos to a portable RFID reader to recognize various facial gestures corresponding to distinct classes of sounds. We then develop natural language processing models that infer meaningful words and sentences based on the observed series of gestures. A detailed user study with 10 users reveals 86% accuracy in reconstructing the top-100 words in the English language, even without the users making any sounds.

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Cited By

Zhang QLan YGuo KWang D(2024)Lipwatch: Enabling Silent Speech Recognition on Smartwatches using Acoustic SensingProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36596148:2(1-29)Online publication date: 15-May-2024
https://doi.org/10.1145/3659614
Bai YShahid ITakawale HRoy N(2024)ScribeProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314117:4(1-31)Online publication date: 12-Jan-2024
https://doi.org/10.1145/3631411
Su YZhang TFeng JShi YYang XWu T(2024)Tagnoo: Enabling Smart Room-Scale Environments with RFID-Augmented PlywoodProceedings of the CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642356(1-18)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642356
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Index Terms

RFID Tattoo: A Wireless Platform for Speech Recognition
1. Human-centered computing
  1. Accessibility
    1. Accessibility technologies
  2. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools
2. Networks
  1. Network services

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 3, Issue 4

December 2019

873 pages

EISSN:2474-9567

DOI:10.1145/3375704

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Copyright © 2019 ACM.

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Published: 14 September 2020

Published in IMWUT Volume 3, Issue 4

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Cited By

Zhang QLan YGuo KWang D(2024)Lipwatch: Enabling Silent Speech Recognition on Smartwatches using Acoustic SensingProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36596148:2(1-29)Online publication date: 15-May-2024
https://doi.org/10.1145/3659614
Bai YShahid ITakawale HRoy N(2024)ScribeProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36314117:4(1-31)Online publication date: 12-Jan-2024
https://doi.org/10.1145/3631411
Su YZhang TFeng JShi YYang XWu T(2024)Tagnoo: Enabling Smart Room-Scale Environments with RFID-Augmented PlywoodProceedings of the CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642356(1-18)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642356
Wang XSu ZRekimoto JZhang Y(2024)Watch Your Mouth: Silent Speech Recognition with Depth SensingProceedings of the CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642092(1-15)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642092
Jiao WWang JHe YXi XWang FFang DChen X(2024)Eliminating Design Effort: A Reconfigurable Sensing Framework for Chipless, Backscatter TagsIEEE/ACM Transactions on Networking10.1109/TNET.2023.332026332:2(1155-1170)Online publication date: Apr-2024
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Sun XXiong JFeng CLi HWu YFang DChen X(2024)EarSSR: Silent Speech Recognition via EarphonesIEEE Transactions on Mobile Computing10.1109/TMC.2024.335671923:8(8493-8507)Online publication date: Aug-2024
https://doi.org/10.1109/TMC.2024.3356719
Yin YWang ZXia KXie LLu S(2024)Acoustic-based Lip Reading for Mobile Devices: Dataset, Benchmark and A Self Distillation-based ApproachIEEE Transactions on Mobile Computing10.1109/TMC.2023.3294416(1-18)Online publication date: 2024
https://doi.org/10.1109/TMC.2023.3294416
Ma ZZhang SLiu JLiu XWang WWang JGuo S(2024)RF-Siamese: Approaching Accurate RFID Gesture Recognition With One SampleIEEE Transactions on Mobile Computing10.1109/TMC.2022.321748723:1(797-811)Online publication date: Jan-2024
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Meegahapola L(2024)Jingxian Wang: “Pushing the Limits of Battery-Free Internet-of-Things”IEEE Pervasive Computing10.1109/MPRV.2024.338395523:1(70-72)Online publication date: Jan-2024
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Kadyrbek NMansurova MShomanov AMakharova G(2023)The Development of a Kazakh Speech Recognition Model Using a Convolutional Neural Network with Fixed Character Level FiltersBig Data and Cognitive Computing10.3390/bdcc70301327:3(132)Online publication date: 20-Jul-2023
https://doi.org/10.3390/bdcc7030132
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