Live Demonstration: Speech reconstruction for speech impaired individuals using Assistive Magnetic Skin System

Montserrat Ramirez De Angel; Abdullah S. Almansouri; Khaled Nabil Salama

doi:10.1109/BioCAS58349.2023.10388857

Live Demonstration: Speech reconstruction for speech impaired individuals using Assistive Magnetic Skin System

Montserrat Ramirez De Angel^*, Abdullah S. Almansouri, Khaled Nabil Salama

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

People diagnosed with a speech-sound disorder (SSD) may have any combination of problems creating or forming speech sounds needed to communicate with others, resulting in frustration, depression and social isolation. Enhanced by advances in artificial wearable skins and machine learning, natural verbal communication for SSD afflicted individuals is more feasible than ever before. An Assistive Magnetic Skin System (AM2S) is designed to assist speech impaired individuals to communicate with others by reading the mouth movement. The system measures the changes in the magnetic skin patches attached next to the lower lip through magnetic field sensors embedded in Magnetphones. The measured magnetic field signal data is processed using a Fine k-Nearest Neighbor (KNN) classifier model. Ultimately, the classified data can be deployed visually on a display or verbally on speakers. AM2S successfully identifies full English alphabets with an average accuracy rate of 94.96%.

Original language	English (US)
Title of host publication	BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350300260
DOIs	https://doi.org/10.1109/BioCAS58349.2023.10388857
State	Published - 2023
Event	2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023 - Toronto, Canada Duration: Oct 19 2023 → Oct 21 2023

Publication series

Name	BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings

Conference

Conference	2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023
Country/Territory	Canada
City	Toronto
Period	10/19/23 → 10/21/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

machine learning
magnetic skin
wearable sensors

ASJC Scopus subject areas

Signal Processing
Biomedical Engineering
Electrical and Electronic Engineering
Clinical Neurology
Neurology

Access to Document

10.1109/BioCAS58349.2023.10388857

Cite this

Angel, M. R. D., Almansouri, A. S., & Salama, K. N. (2023). Live Demonstration: Speech reconstruction for speech impaired individuals using Assistive Magnetic Skin System. In BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings (BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BioCAS58349.2023.10388857

Angel, Montserrat Ramirez De ; Almansouri, Abdullah S. ; Salama, Khaled Nabil. / Live Demonstration : Speech reconstruction for speech impaired individuals using Assistive Magnetic Skin System. BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings).

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title = "Live Demonstration: Speech reconstruction for speech impaired individuals using Assistive Magnetic Skin System",

abstract = "People diagnosed with a speech-sound disorder (SSD) may have any combination of problems creating or forming speech sounds needed to communicate with others, resulting in frustration, depression and social isolation. Enhanced by advances in artificial wearable skins and machine learning, natural verbal communication for SSD afflicted individuals is more feasible than ever before. An Assistive Magnetic Skin System (AM2S) is designed to assist speech impaired individuals to communicate with others by reading the mouth movement. The system measures the changes in the magnetic skin patches attached next to the lower lip through magnetic field sensors embedded in Magnetphones. The measured magnetic field signal data is processed using a Fine k-Nearest Neighbor (KNN) classifier model. Ultimately, the classified data can be deployed visually on a display or verbally on speakers. AM2S successfully identifies full English alphabets with an average accuracy rate of 94.96%.",

keywords = "machine learning, magnetic skin, wearable sensors",

author = "Angel, {Montserrat Ramirez De} and Almansouri, {Abdullah S.} and Salama, {Khaled Nabil}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023 ; Conference date: 19-10-2023 Through 21-10-2023",

year = "2023",

doi = "10.1109/BioCAS58349.2023.10388857",

language = "English (US)",

series = "BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings",

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Angel, MRD, Almansouri, AS & Salama, KN 2023, Live Demonstration: Speech reconstruction for speech impaired individuals using Assistive Magnetic Skin System. in BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings. BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023, Toronto, Canada, 10/19/23. https://doi.org/10.1109/BioCAS58349.2023.10388857

Live Demonstration: Speech reconstruction for speech impaired individuals using Assistive Magnetic Skin System. / Angel, Montserrat Ramirez De; Almansouri, Abdullah S.; Salama, Khaled Nabil.
BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2023. (BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Live Demonstration

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AU - Angel, Montserrat Ramirez De

AU - Almansouri, Abdullah S.

AU - Salama, Khaled Nabil

PY - 2023

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N2 - People diagnosed with a speech-sound disorder (SSD) may have any combination of problems creating or forming speech sounds needed to communicate with others, resulting in frustration, depression and social isolation. Enhanced by advances in artificial wearable skins and machine learning, natural verbal communication for SSD afflicted individuals is more feasible than ever before. An Assistive Magnetic Skin System (AM2S) is designed to assist speech impaired individuals to communicate with others by reading the mouth movement. The system measures the changes in the magnetic skin patches attached next to the lower lip through magnetic field sensors embedded in Magnetphones. The measured magnetic field signal data is processed using a Fine k-Nearest Neighbor (KNN) classifier model. Ultimately, the classified data can be deployed visually on a display or verbally on speakers. AM2S successfully identifies full English alphabets with an average accuracy rate of 94.96%.

AB - People diagnosed with a speech-sound disorder (SSD) may have any combination of problems creating or forming speech sounds needed to communicate with others, resulting in frustration, depression and social isolation. Enhanced by advances in artificial wearable skins and machine learning, natural verbal communication for SSD afflicted individuals is more feasible than ever before. An Assistive Magnetic Skin System (AM2S) is designed to assist speech impaired individuals to communicate with others by reading the mouth movement. The system measures the changes in the magnetic skin patches attached next to the lower lip through magnetic field sensors embedded in Magnetphones. The measured magnetic field signal data is processed using a Fine k-Nearest Neighbor (KNN) classifier model. Ultimately, the classified data can be deployed visually on a display or verbally on speakers. AM2S successfully identifies full English alphabets with an average accuracy rate of 94.96%.

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T3 - BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings

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Angel MRD, Almansouri AS, Salama KN. Live Demonstration: Speech reconstruction for speech impaired individuals using Assistive Magnetic Skin System. In BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2023. (BioCAS 2023 - 2023 IEEE Biomedical Circuits and Systems Conference, Conference Proceedings). doi: 10.1109/BioCAS58349.2023.10388857

Live Demonstration: Speech reconstruction for speech impaired individuals using Assistive Magnetic Skin System

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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