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A Dataset and TinyML Model for Coarse Age Classification Based on Voice Commands

Classification (of information); Data acquisition; Internet of things; Learning systems; Statistical tests; Age classification; Arduino nano BLE 33 sense; Data collection; Data preprocessing; Edge impulse; Machine learning models; Machine-learning; Sub-disciplines; Tiny machine learning; Voice comma...

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Main Authors: Kadir A.D.I.A., Al-Haiqi A., Din N.M.
Other Authors: 57426768900
Format: Conference Paper
Published: Institute of Electrical and Electronics Engineers Inc. 2023
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spelling my.uniten.dspace-263982023-05-29T17:09:59Z A Dataset and TinyML Model for Coarse Age Classification Based on Voice Commands Kadir A.D.I.A. Al-Haiqi A. Din N.M. 57426768900 57510682900 9335429400 Classification (of information); Data acquisition; Internet of things; Learning systems; Statistical tests; Age classification; Arduino nano BLE 33 sense; Data collection; Data preprocessing; Edge impulse; Machine learning models; Machine-learning; Sub-disciplines; Tiny machine learning; Voice command; Deep learning This study explores the emerging sub-discipline of Tiny Machine Learning (TinyML) in the specific context of classifying audio data. New problems arise from the anticipation of voice prevalence in future interfaces with machines, especially embedded ones, and the need to have embedded intelligence into those machines, which can be captured by the idea of TinyML. In particular, there is a lack of studies on TinyML models for age classification based on voice commands, especially involving children as subjects. There is also a lack of datasets that include voice commands of both adults and children. This study aims to develop a TinyML model that is able to discriminate adults from children from their voice commands. The methodology follows the workflow of building deep learning models, including data collection and preprocessing, training, testing and deployment. Beyond the tools used for data collection and preprocessing, Edge Impulse was adopted as the development platform to train and test the model. The evaluation of the model showed a classification accuracy of more than 97% based on the custom dataset built to train and test the model. Finally, the tiny model was successfully deployed and evaluated on an Arduino Nano 33 BLE sense microcontroller. � 2021 IEEE Final 2023-05-29T09:09:58Z 2023-05-29T09:09:58Z 2021 Conference Paper 10.1109/MICC53484.2021.9642091 2-s2.0-85123943605 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123943605&doi=10.1109%2fMICC53484.2021.9642091&partnerID=40&md5=6266300f8768436ae5407113a1015fed https://irepository.uniten.edu.my/handle/123456789/26398 75 80 Institute of Electrical and Electronics Engineers Inc. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Classification (of information); Data acquisition; Internet of things; Learning systems; Statistical tests; Age classification; Arduino nano BLE 33 sense; Data collection; Data preprocessing; Edge impulse; Machine learning models; Machine-learning; Sub-disciplines; Tiny machine learning; Voice command; Deep learning
author2 57426768900
author_facet 57426768900
Kadir A.D.I.A.
Al-Haiqi A.
Din N.M.
format Conference Paper
author Kadir A.D.I.A.
Al-Haiqi A.
Din N.M.
spellingShingle Kadir A.D.I.A.
Al-Haiqi A.
Din N.M.
A Dataset and TinyML Model for Coarse Age Classification Based on Voice Commands
author_sort Kadir A.D.I.A.
title A Dataset and TinyML Model for Coarse Age Classification Based on Voice Commands
title_short A Dataset and TinyML Model for Coarse Age Classification Based on Voice Commands
title_full A Dataset and TinyML Model for Coarse Age Classification Based on Voice Commands
title_fullStr A Dataset and TinyML Model for Coarse Age Classification Based on Voice Commands
title_full_unstemmed A Dataset and TinyML Model for Coarse Age Classification Based on Voice Commands
title_sort dataset and tinyml model for coarse age classification based on voice commands
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2023
_version_ 1806423272568389632
score 13.211869

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