Audio Spectrogram Transformer-based Audio Classification using Voice data of Dementia Patients

Younjeong Lee; Chanho Park; Yeeun Moon; Jongpil Jeong

doi:10.1109/BCD57833.2023.10466301

Audio Spectrogram Transformer-based Audio Classification using Voice data of Dementia Patients

Younjeong Lee
, Chanho Park
, Yeeun Moon
, Jongpil Jeong

Research & Business Foundation

Sungkyunkwan University

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

3 Scopus citations

Abstract

Globally, aging is ongoing, and the probability of senile disease and dementia patients continue to increase as human lifespan and the proportion of the elderly increase. Dementia is a disease that affects the depression and quality of life of the elderly, and it is a socially and economically dangerous disease that cannot live independently. Currently, the only treatment for dementia is through training if the disease is delayed or detected early. Diagnosing dementia early is the most important step at this point, and studies are currently being conducted non-face-To-face or through voice. This study aims to predict dementia early through human voice. The study was conducted with the aim of optimizing and lightening the characteristics of dementia patients by applying the Audio Spectrogram Transformer analysis model as a voice classification model. The model used in this paper classifies dementia with an accuracy of 89%. In future research, we will try a study that combines Explainable AI (XAI), an interpretable artificial intelligence of deep learning.

Original language	English
Title of host publication	2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023
Editors	Jongwoo Park, Ngo Thi Phuong Lan, Sungtaek Lee, Tran Anh Tien, Jongbae Kim
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	114-119
Number of pages	6
ISBN (Electronic)	9798350373615
DOIs	https://doi.org/10.1109/BCD57833.2023.10466301
State	Published - 2023
Event	8th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023 - Ho Chi Minh City, Viet Nam Duration: 14 Dec 2023 → 16 Dec 2023

Publication series

Name	2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023

Conference

Conference	8th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023
Country/Territory	Viet Nam
City	Ho Chi Minh City
Period	14/12/23 → 16/12/23

Keywords

Audio Classification
Audio Processing
Audio Transformer
Dementia
Mel-Spectrogram

Access to Document

10.1109/BCD57833.2023.10466301

Cite this

Lee, Y., Park, C., Moon, Y., & Jeong, J. (2023). Audio Spectrogram Transformer-based Audio Classification using Voice data of Dementia Patients. In J. Park, N. T. P. Lan, S. Lee, T. A. Tien, & J. Kim (Eds.), 2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023 (pp. 114-119). (2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BCD57833.2023.10466301

Lee, Younjeong ; Park, Chanho ; Moon, Yeeun et al. / Audio Spectrogram Transformer-based Audio Classification using Voice data of Dementia Patients. 2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023. editor / Jongwoo Park ; Ngo Thi Phuong Lan ; Sungtaek Lee ; Tran Anh Tien ; Jongbae Kim. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 114-119 (2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023).

@inproceedings{506c7532e20f426c910bcaaa8688890c,

title = "Audio Spectrogram Transformer-based Audio Classification using Voice data of Dementia Patients",

abstract = "Globally, aging is ongoing, and the probability of senile disease and dementia patients continue to increase as human lifespan and the proportion of the elderly increase. Dementia is a disease that affects the depression and quality of life of the elderly, and it is a socially and economically dangerous disease that cannot live independently. Currently, the only treatment for dementia is through training if the disease is delayed or detected early. Diagnosing dementia early is the most important step at this point, and studies are currently being conducted non-face-To-face or through voice. This study aims to predict dementia early through human voice. The study was conducted with the aim of optimizing and lightening the characteristics of dementia patients by applying the Audio Spectrogram Transformer analysis model as a voice classification model. The model used in this paper classifies dementia with an accuracy of 89\%. In future research, we will try a study that combines Explainable AI (XAI), an interpretable artificial intelligence of deep learning.",

keywords = "Audio Classification, Audio Processing, Audio Transformer, Dementia, Mel-Spectrogram",

author = "Younjeong Lee and Chanho Park and Yeeun Moon and Jongpil Jeong",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 8th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023 ; Conference date: 14-12-2023 Through 16-12-2023",

year = "2023",

doi = "10.1109/BCD57833.2023.10466301",

language = "English",

series = "2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023",

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

pages = "114--119",

editor = "Jongwoo Park and Lan, \{Ngo Thi Phuong\} and Sungtaek Lee and Tien, \{Tran Anh\} and Jongbae Kim",

booktitle = "2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023",

}

Lee, Y, Park, C, Moon, Y & Jeong, J 2023, Audio Spectrogram Transformer-based Audio Classification using Voice data of Dementia Patients. in J Park, NTP Lan, S Lee, TA Tien & J Kim (eds), 2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023. 2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023, Institute of Electrical and Electronics Engineers Inc., pp. 114-119, 8th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023, Ho Chi Minh City, Viet Nam, 14/12/23. https://doi.org/10.1109/BCD57833.2023.10466301

Audio Spectrogram Transformer-based Audio Classification using Voice data of Dementia Patients. / Lee, Younjeong; Park, Chanho; Moon, Yeeun et al.
2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023. ed. / Jongwoo Park; Ngo Thi Phuong Lan; Sungtaek Lee; Tran Anh Tien; Jongbae Kim. Institute of Electrical and Electronics Engineers Inc., 2023. p. 114-119 (2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023).

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

TY - GEN

T1 - Audio Spectrogram Transformer-based Audio Classification using Voice data of Dementia Patients

AU - Lee, Younjeong

AU - Park, Chanho

AU - Moon, Yeeun

AU - Jeong, Jongpil

PY - 2023

Y1 - 2023

N2 - Globally, aging is ongoing, and the probability of senile disease and dementia patients continue to increase as human lifespan and the proportion of the elderly increase. Dementia is a disease that affects the depression and quality of life of the elderly, and it is a socially and economically dangerous disease that cannot live independently. Currently, the only treatment for dementia is through training if the disease is delayed or detected early. Diagnosing dementia early is the most important step at this point, and studies are currently being conducted non-face-To-face or through voice. This study aims to predict dementia early through human voice. The study was conducted with the aim of optimizing and lightening the characteristics of dementia patients by applying the Audio Spectrogram Transformer analysis model as a voice classification model. The model used in this paper classifies dementia with an accuracy of 89%. In future research, we will try a study that combines Explainable AI (XAI), an interpretable artificial intelligence of deep learning.

AB - Globally, aging is ongoing, and the probability of senile disease and dementia patients continue to increase as human lifespan and the proportion of the elderly increase. Dementia is a disease that affects the depression and quality of life of the elderly, and it is a socially and economically dangerous disease that cannot live independently. Currently, the only treatment for dementia is through training if the disease is delayed or detected early. Diagnosing dementia early is the most important step at this point, and studies are currently being conducted non-face-To-face or through voice. This study aims to predict dementia early through human voice. The study was conducted with the aim of optimizing and lightening the characteristics of dementia patients by applying the Audio Spectrogram Transformer analysis model as a voice classification model. The model used in this paper classifies dementia with an accuracy of 89%. In future research, we will try a study that combines Explainable AI (XAI), an interpretable artificial intelligence of deep learning.

KW - Audio Classification

KW - Audio Processing

KW - Audio Transformer

KW - Dementia

KW - Mel-Spectrogram

UR - https://www.scopus.com/pages/publications/85189933718

U2 - 10.1109/BCD57833.2023.10466301

DO - 10.1109/BCD57833.2023.10466301

M3 - Conference contribution

AN - SCOPUS:85189933718

T3 - 2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023

SP - 114

EP - 119

BT - 2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023

A2 - Park, Jongwoo

A2 - Lan, Ngo Thi Phuong

A2 - Lee, Sungtaek

A2 - Tien, Tran Anh

A2 - Kim, Jongbae

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 8th IEEE/ACIS International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023

Y2 - 14 December 2023 through 16 December 2023

ER -

Lee Y, Park C, Moon Y, Jeong J. Audio Spectrogram Transformer-based Audio Classification using Voice data of Dementia Patients. In Park J, Lan NTP, Lee S, Tien TA, Kim J, editors, 2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 114-119. (2023 IEEE/ACIS 8th International Conference on Big Data, Cloud Computing, and Data Science, BCD 2023). doi: 10.1109/BCD57833.2023.10466301

Audio Spectrogram Transformer-based Audio Classification using Voice data of Dementia Patients

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Keywords

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